Question 4:

The dataset "_data2" contains information about score, study hours, age of student, family income, and whether the student participated in an after-school education program for a sample of students, which are randomly chosen from a large population.

To understand how the percentage change in study hours affects the percentage change in scores, run a nonlinear regression with exam score on study hours to find the elasticity between study hours and score. Assume the significance level is 5%.

1. The regression equation is _ _ ___

1. Analyze the summary of regression results (i.e. state the estimated value of regression coefficients, determine if each regression coefficient is different from zero for population by using t-value or P-value, interpret the use of adjusted R-squared). Summarize the effect of percentage change in study hours on the percentage change in score.

1. Screenshot the code and results.

ID	score	study_hours	age	family_income	joined_program
1	66	5	18	1500	Yes
2	77	5	19	13000	Yes
3	79	5	21	8000	No
4	87	6	19	9000	Yes
5	40	3	21	7500	Yes
6	31	1	18	8000	No
7	97	7	21	13000	No
8	42	3	19	3500	No
9	96	8	22	14000	Yes
10	77	5	20	10000	Yes
11	60	3	18	7200	Yes
12	87	6	20	14600	Yes
13	99	8	19	13080	No
14	25	1	20	7200	No
15	100	9	23	13400	Yes
16	42	3	18	1700	No
17	60	4	23	1600	Yes
18	57	4	19	1800	No
19	50	3	23	8000	Yes
20	72	5	20	1400	Yes
21	46	3	18	1400	Yes
22	39	1	24	1400	No
23	42	3	25	8500	No
24	87	6	19	11000	Yes
25	30	1	18	6600	No
26	42	3	18	700	Yes
27	76	5	19	15300	No
28	47	3	21	1500	Yes
29	72	5	19	5500	Yes
30	42	3	21	11000	Yes
31	57	4	18	5800	No
32	55	1	21	6600	No
33	80	5	19	6900	Yes
34	98	9	22	8500	No
35	27	2	20	6200	Yes
36	72	5	18	8600	No
37	87	6	20	16000	Yes
38	100	9	19	10500	Yes
39	57	4	20	13000	Yes
40	72	5	23	8000	No
41	27	2	18	6300	No
42	100	10	26	14000	Yes
43	88	9	18	21000	No
44	57	4	22	1800	Yes
45	38	2	22	5500	No
46	57	4	18	11000	Yes
47	80	12	21	12000	Yes
48	100	10	22	14000	Yes
49	89	7	18	16000	No
50	87	7	18	16000	Yes