Problem 1. Sarcoidosis is a disease characterized by the growth of tiny collections of inflammatory cells (granulomas) in any part of a human body, most commonly the lungs and lymph nodes. But it can also affect the eyes, skin, heart, and other organs. Data were collected from 60 patients who were admitted to a hospital with suspected cardiac sarcoidosis. The measurements were age (in years), gender (F/M), ethnic descent (Black/White/Asian), family history of cardiac sarcoidosis (no/yes), the number of symptoms (chest pain, shortness of breath, fainting, fatigue, and irregular heartbeats), and whether was diagnosed with cardiac sarcoidosis (no/yes). Use the included code and output when answering the questions below. (a) State the fitted model. Give estimates of all parameters. What is the name of this model? What predictors are significant at the 5% level? (b) Give the interpretation of the significant estimated beta coefficients. Describe the profile of a patient who has the largest chance to be diagnosed with cardiac sarcoidosis. (c) Predict the probability of being diagnosed with cardiac sarcoidosis for a 52-year old Black female patient whose mother had been diagnosed with the disease and who currently doesn't show any symptoms herself. Do prediction by hand and compare the result to the one given in R.

Help me solve this question. I will attach the code at below.