Question

An association was formed by students to protest labor exploitation in the apparel industry. There were 18 student "sit-ins" for a "sweat-free campus" organized at several universities. Data were collected for the duration (in days) of each sit-in, as well as the number of student arrests. The data for 5 sit-ins in which there was at least one arrest and the results of a simple linear regression are found below. Let y be the number of arrests and x be the duration. Complete parts a through d Click the icon to view the data table E Click the icon to view the results of the simple linear regression. a. Write the equation of a straight-line model relating y to x.A. y = beta1xB. y = beta1x^2 + beta0C. y = beta0 + beta1x + {D. y = beta1x + {b. Use the results of the linear regression to find the least squares prediction equation Type an integer or decimal rounded to three decimal places as needed)

Answer 1

The question addresses using a simple linear regression model to determine the relationship between two variables, and how to interpret the parameters of that model, as well as the significance of the correlation coefficient in the context of a hypothetical student protest situation.

Step-by-step explanation:

The subject of this question is about linear regression analysis in mathematics, particularly in the context of statistical analysis. The question demonstrates the application of a simple linear regression to decipher the relationship between the duration of student sit-ins (independent variable) and the number of arrests (dependent variable).

Answers to the Linear Regression Exercise:

1. The equation of the straight-line model relating number of arrests (y) to duration (x) is C. y = beta0 + beta1x, where beta0 is the y-intercept, and beta1 is the slope of the regression line.
2. To find the least squares prediction equation, use the provided regression output to plug in the estimated coefficients for the y-intercept (beta0) and slope (beta1). The form it should take is ý = a + bx, where 'a' is the estimated y-intercept and 'b' is the estimated slope.
3. The y-intercept, or the constant 'a', has meaning if it has a context within the scope of the study. For example, it might represent the expected number of arrests when the duration of the sit-in is zero, if such a scenario makes sense within the context of the study.
4. To find the correlation coefficient, typically denoted as 'r', refer to the regression output and assess its significance level. A significant correlation coefficient indicates a strong relationship between the dependent and independent variables.

Answer 2

Data for complete question is attached.

Answers

Therefore .

A. The regression equation is

y = beta0 + beta1+ ∈

B. From the given output regression line

y= 2.478+7.717x