GUVI-Assignment_5_6_7

Assignment 5: Ground Cricket Chirps Analysis

Overview

This assignment involves analyzing chirp frequency data of striped ground crickets in relation to ground temperatures. The data suggests a correlation between temperature and chirp frequency, as crickets are ectotherms. The goal is to find a linear regression equation, chart the data and equation, calculate the R-squared score for correlation assessment, and perform extrapolation and interpolation.

Data Source

The data was obtained from "The Song of Insects" (1948) by George W. Pierce, who measured chirp frequency at various ground temperatures.

Tasks

1. Linear Regression Equation: Find the linear regression equation for the data.
2. Chart Data and Equation: Plot the original data and overlay the linear regression equation on the chart.
3. R-squared Score: Calculate the R-squared score to assess the strength of correlation.
4. Extrapolation: Predict chirp frequency at a ground temperature of 95º F.
5. Interpolation: Determine the ground temperature for a chirp frequency of 18 chirps per second.

Assignment 6: Brain vs. Body Weight Analysis

Overview

In this assignment, the average brain and body weights for various mammal species are recorded in the file brain_body.txt. The goal is to perform a linear regression analysis to understand the relationship between brain weight and body weight.

Data Source

The data is sourced from brain_body.txt, containing measurements for different mammal species.

Tasks

1. Linear Regression Equation: Find the linear regression equation for the relationship between brain weight and body weight.
2. Chart Data and Equation: Plot the original data points and overlay the linear regression equation on the chart.
3. R-squared Score: Calculate the R-squared score to assess the strength of correlation.

Assignment 7: Salary Discrimination Analysis

Overview

The file salary.txt contains data for 52 tenure-track professors at a small Midwestern college. This data was used in legal proceedings in the 1980s about discrimination against women in salary. The dataset includes information on sex, rank, years, degree, years since highest degree, and salary.

Data Source

The data is sourced from salary.txt, containing information about tenure-track professors.

Tasks

1. Linear Regression Equation: Find the linear regression equation using columns 1-5 to predict column 6 (Salary).
2. Best Column Selection: Determine the selection of columns that provides the highest R-squared score for regression.
3. Sex as a Factor: Analyze if sex is a significant factor affecting salary.