A charitable organisation in the Netherlands would like to know the factors affecting response to a fundraising campaign. In 2001, the charity sent requests for donations to 4,268 donors for one fundraising initiative. The results were recorded in the file, "charity.dta". The charity wants to understand the difference between those who responded and those who did not. They suspect exposure to their previous marketing efforts or donors' generosity would affect the gift amount. Below is the first model they want to estimate. = + 1 + The variable "gift" is the amount donated to the initiative in Netherland Guilders. The variable "gift" would equal zero in the dataset if no amount were received. Otherwise, it will have the value of the amount given. The variable "mailsyear" was the average number of mail campaigns sent to the donor across four years. The charity proposes that the more donors are exposed to their campaigns, the more they will become more familiar with their work, and more significant donations will be made. The next model they want to estimate is below, where "avgdonate" is the average amount donated across four years. Some of the staff in the charity believe that the amount given will be based on how generous donors are. The gifts will be more significant if they have historically donated large amounts. = + 1 + The charity wants to determine whether exposure or human nature affects the amount of gift received from donors. They want the models to be estimated model and interpreted

question 2:. How well does the model explain the amount donated to the initiative?