please help. thank you

1. This week, Randy wants to investigate the determinants of the demand for publictransportation in South Park. In 2019, he collected the following data for a sample of n = 100 South Park residents: annual expenditures on public transport (expend, in dollars), number or days worked during the year (worked), and number of days not worked during the year (no tworked). (a) Initially, Randy tries to estimate the following model: expend = 30 + 1worked + znotworked + u but he fails. Explain why Randy is unable to estimate this model. (Hint: can there be a linear relationship between the explanatory variables?) (b) The Randy decides to split the number of days not worked into the number of daysnot worked due to illness (ill) and the number of days not worked due to other reasons (other), and estimates the following model: expend = 30 + ,81W0rked + ,620ther + u by OLS, so here are the results: A expend : 9.6 + 2.10w0rked + 0.450ther (8.3) (1.98) (1.77) n = 100,R2= 0.72 (i) Test the null hypothesis that the coefficient for worked is zero against a two- sided alternative at the 5% level. (ii) Test the null hypothesis that the coefficient for other is zero against a twosided alternative at the 5% level. (iii) Is Randy's model overall significant at the 5% level? (iv) In Randy's data set of 100 South Park residents, sample mean of ill is 2.1, while the sample mean of other is 120.2. Can you reconcile your findings in (i), (ii) and (iii)? (Hint: Do you think that other and worked are highly correlated? What does it mean for standard errors of our OLS estimates?)