Crowdlending: Credit Score (15 points) Bob, a micro-entrepreneur who runs a local convenient store at Baltimore, is planning to open his second store in a nearby neighborhood. He is considering borrowing money to fund his second store from a crowdlending platform where he has been maintaining a good credit history. Bob knows how the platform determines initiators' (borrowers') loan interest rates. However, he is not familiar with how initiators' (borrowers') credit scores are calculated on this platform. He would like to seek some insights about this. You, a student has taken class 1 to 13 of MKTG/BADM 3661, are asked to help Bob understand the issue. You collect the following data from the crowdlending platform: 1 able 1: Sata trom Crowdiending Plattorm You calculate the mean, standard deviation, minimum, and maximum for "score" in Excel and get the following results: Then, you perform a regression analysis for "score" in Excel and get the following results: Table 2: Multivariable Regression Results 1. Bob tells you that his credit score is 55. Then, he says "more than half of the initiators in the data have a credit score less than his (credit score)." Based on the data analysis above, can you tell whether Bob's statement (i.e., the underlined statement) is true or false? If yes, please tell whether Bob's statement is true or false; if not, please explain why. (4 points) 2. Based on your regression results in Table 2, which variables have significant effects on the credit score? (Note: You only need to name the variables.) (5 points) 3. Peter is a friend of Bob, who is new to the United States of America. Peter is not a U.S. citizen, and he is not a permanent resident of U.S. as well. Peter is considering borrowing money from the same crowdlending platform to support his business initiatives. Peter knows that he is younger than Bob, so he asks you the following question during his consultation with you: "Does a lower age help decrease my credit score on this platform? Please advise." Can you use the available data and analysis results to answer Peter's question? If yes, please answer Peter's question; if no, please explain why. (6 points) Crowdlending: Credit Score (15 points) Bob, a micro-entrepreneur who runs a local convenient store at Baltimore, is planning to open his second store in a nearby neighborhood. He is considering borrowing money to fund his second store from a crowdlending platform where he has been maintaining a good credit history. Bob knows how the platform determines initiators' (borrowers') loan interest rates. However, he is not familiar with how initiators' (borrowers') credit scores are calculated on this platform. He would like to seek some insights about this. You, a student has taken class 1 to 13 of MKTG/BADM 3661, are asked to help Bob understand the issue. You collect the following data from the crowdlending platform: 1 able 1: Sata trom Crowdiending Plattorm You calculate the mean, standard deviation, minimum, and maximum for "score" in Excel and get the following results: Then, you perform a regression analysis for "score" in Excel and get the following results: Table 2: Multivariable Regression Results 1. Bob tells you that his credit score is 55. Then, he says "more than half of the initiators in the data have a credit score less than his (credit score)." Based on the data analysis above, can you tell whether Bob's statement (i.e., the underlined statement) is true or false? If yes, please tell whether Bob's statement is true or false; if not, please explain why. (4 points) 2. Based on your regression results in Table 2, which variables have significant effects on the credit score? (Note: You only need to name the variables.) (5 points) 3. Peter is a friend of Bob, who is new to the United States of America. Peter is not a U.S. citizen, and he is not a permanent resident of U.S. as well. Peter is considering borrowing money from the same crowdlending platform to support his business initiatives. Peter knows that he is younger than Bob, so he asks you the following question during his consultation with you: "Does a lower age help decrease my credit score on this platform? Please advise." Can you use the available data and analysis results to answer Peter's question? If yes, please answer Peter's question; if no, please explain why. (6 points)
