Linear regression for charges vs days in the hospital


Discuss the below:

Q1. Do charges incurred by a patient depend on the type of insurance the patient has? If so, how? This is a hypothesis test where we could examine the average charges for patients with "managed care" vs. average charges for patients with "commercial" insurance.

Q2. Do charges incurred by patients depend on which doctor treats them? If so, how? We could create a confidence interval for each doctor, then see if the true population mean for each could be the same. If not, which doctor is most expensive?

Q3.What is an appropriate linear regression for Charges vs. Days in the hospital? Are Charges related to Days, Physician, and/or Payor? If so, how?

VARIABLE MEANING

DAYS is the number of days the patient spent in the hospital.

CHRGS is the total expenses charged to that patient

PHYS is a code identifying the physician

PAYOR indicated the type of insurance the patient carried:

1 for managed care and 0 for commercial insurance.

DAYS CHRGS PHYS PAYOR
2 1701 10 0
2 3500 4 1
2 3165 10 0
1 1953 14 1
2 2607 2 1
2 2944 12 1
4 5063 2 1
2 2396 13 1
4 4903 2 1
2 2280 7 1
2 2939 7 1
3 3585 4 1
2 3073 13 1
2 2880 14 1
2 2358 10 0
3 3418 2 1
3 3604 2 0
3 3480 6 1
2 3306 10 0
3 3047 4 1
2 2157 11 1
2 2439 4 1
3 2647 11 1
2 1874 6 1
1 2139 10 1
2 2424 14 1
2 2450 12 1
2 2198 14 0
2 3355 10 1
2 2609 4 0
2 2324 2 1
2 2207 12 1
2 2649 11 0
3 3375 10 1
2 3906 6 1
3 4049 14 1
2 2564 13 1
2 2745 11 1
3 1254 6 1
2 2953 2 1
2 2334 7 1
2 2809 7 1
2 929 13 1
3 3464 14 1
2 3173 10 0
2 3034 14 1
2 3716 12 1
2 2137 6 1
3 3430 6 1
3 3041 6 1
2 2247 12 1
3 4357 12 1
2 3050 12 1
2 2779 12 1
2 2357 4 1
2 2620 7 1
3 3369 13 1
2 3090 7 1
4 6340 11 1
2 2900 10 1
3 3709 2 1
3 3503 4 1
2 2991 12 1
2 2941 14 1
2 2668 14 1
2 2138 2 1
2 2227 12 0
2 2838 10 0
2 2681 2 0
3 3945 7 1
2 2026 4 0
3 3160 10 1
2 3270 12 0
3 4146 6 1
2 3757 11 1
2 2435 7 1
2 2343 10 1
3 3932 2 1
2 2285 10 1
2 3001 14 1
2 1864 7 0
3 4711 12 1
3 3283 2 0
2 2592 7 1
1 2081 12 1
1 1791 14 1
2 3729 2 1
2 2117 10 1
3 4510 11 1
2 2017 7 1
2 3118 14 1
3 3392 2 1
2 1854 4 1
14 14898 2 1
3 3819 2 1
3 2644 4 1
3 2331 13 0
3 3492 11 1
2 2666 7 0
3 4248 2 1
3 2500 4 1
2 3112 10 1
3 2955 7 1
2 2761 14 1
2 1905 2 1
3 3394 10 1
2 3663 10 1
3 3059 6 1
2 2528 10 1
2 2823 2 1
6 6710 11 1
2 2543 13 1
3 2785 2 0
2 2589 12 0
2 3183 11 1
1 1806 10 1
2 3115 10 0
2 3204 7 1
2 2921 2 0
3 4933 2 0
2 4722 13 1
3 5633 13 1
2 2780 10 0
2 2798 4 1
3 2066 7 1
3 2494 11 1
3 2724 10 0
2 2352 11 0
1 1793 7 1
2 2629 4 1
2 3094 14 0
2 2804 2 0
2 2801 13 0
2 2638 7 1
2 2263 10 0
2 2449 11 0
2 2473 11 0
3 2864 6 1
2 2534 11 1
2 2550 10 1
2 3768 12 1
2 3194 10 0
1 2153 12 0
1 1840 7 0
2 2522 12 1
1 2145 12 1
2 2403 6 1
3 3287 2 1
2 2979 6 1
2 3182 7 0
2 2954 10 0
2 2158 11 0
2 3455 12 0
2 2367 14 1
3 2798 10 1
2 2408 11 1
2 2468 11 1
3 3081 12 1
2 2218 7 1
3 2133 11 0
4 5499 13 1
2 2251 12 1
2 2310 11 0
1 2220 11 0
2 2176 10 0
1 2048 2 1
2 2566 11 1
2 2450 11 0
2 2582 11 1
2 2612 7 0
2 2683 6 1
2 2827 14 0
2 3202 10 1
3 3779 10 1
2 2833 12 1
2 3458 10 0
1 2789 7 1
2 1590 7 1
3 3868 7 1
2 3077 12 1
2 3109 10 0
3 2697 4 0
2 3182 13 1
2 3034 6 1
1 2179 14 1
1 2178 7 1
3 4185 11 1
2 1567 10 1
2 2347 14 1
1 2268 10 1
3 3617 2 0
2 2858 10 1
2 2542 10 1
2 2665 7 1
2 2436 6 1
2 2392 12 1
2 2739 7 0
3 2181 12 0
2 2308 4 0
2 3800 13 0
2 2242 12 1
2 2314 7 1
1 1960 6 0
3 4183 11 1
1 1663 4 1
1 2070 7 0
3 2753 6 1
3 2209 6 0
3 3218 10 1
2 2419 13 0
3 3289 11 0
2 2222 4 1
1 2741 4 0
3 3454 10 1
2 3848 10 1
2 2292 7 0
2 2594 7 1
2 2378 6 1
1 902 7 0
3 2935 7 1
2 3230 6 1
2 2219 2 0
3 2687 12 1
2 1848 14 1
3 2891 4 0
2 2698 12 0
2 3032 7 0
1 2886 10 1
1 3381 2 0
2 2752 10 0
1 3675 13 1
2 2840 13 1
2 3105 13 0
2 2288 11 1
2 3128 14 0
2 2289 7 0
2 2602 10 0
2 2604 14 1
2 1023 12 0
1 1899 10 0
2 2334 10 1
2 2310 2 1
3 3636 6 1
2 4206 7 0
2 2414 12 1
2 2206 13 1
3 2907 2 1
2 3017 14 1
2 3050 14 1
2 1973 7 1
2 2692 10 1
3 2564 11 0
2 3693 10 1
2 2741 13 1
2 2888 2 1
2 3279 6 0
3 2873 7 1
2 2582 10 1
2 2640 2 0
1 2068 14 1
2 2123 10 0
3 3480 14 1
3 4475 6 0
2 2312 14 1
2 2898 4 1
3 3708 10 0
1 2078 10 0
2 2570 11 1
3 3639 14 1
2 4674 12 0
2 2534 14 0
2 2797 7 0
2 3139 12 0
3 3826 2 0
2 2067 10 0
2 2840 2 1
2 2465 12 1
1 1947 12 0
1 2167 7 0
2 2840 10 0
2 2711 6 1
2 3137 2 0
1 2955 2 0
2 2563 10 1
1 1924 4 1
1 2062 6 0
2 2663 13 0
1 2184 2 0
2 3064 10 1

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Applied Statistics: Linear regression for charges vs days in the hospital
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