The Statistics Department offers courses at a variety of levels. Suitably prepared undergraduates are welcome to take graduate level classes to meet undergraduate requirements. Enrollment is at the discretion of the instructor, but the options listed below provide suggestions for when accelerated course selections are appropriate. Undergraduates considering taking graduate classes are expected to have grades of at least A- in relevant undergraduate classes.
525/526. These are more advanced versions of 425/430. Students with a strong math background (One semester of analysis ([295 and 296], 297, 351, 395, 451, or equivalent)) can take 525 without taking 425. Students with 525 can take 511 in place of 426.
510/511. These are more advanced versions of 425/426. Students with a strong math background (One semester of analysis ([295 and 296], 297, 351, 395, 451, or equivalent)) are prepared for 510. Students with 510 can take 511 in place of 426. Students majoring in mathematics may prefer to take 525/511 instead.
610 revisits material in 426/511 at a PhD level. Undergraduates with 426 or 511 as well as a strong probability background (say, 510 or 525) and strong math background (say, MATH 551 and MATH 217) have been successful in 610.
621 revisits material in 425/510/525 at a PhD level. Undergraduates with 425/510/525 as well as a strong math background (say, MATH 551) have been successful in 621.
507 is appropriate for students with STATS 306 and EECS 281. It can replace STATS 306 for students with good grades in STATS 413 and EECS 281.
570 can replace 470 for undergraduates who have strong grades in STATS 413 and MATH 217.
600 is appropriate after 413/500 for students with good grades in 426/510, 425/511 and MATH 217. After success in 600, undergraduates could take 601.
503. This is a more advanced version of 415. Students with a strong math background (say, MATH 217 and MATH 451) and good performance in 413/500, 425/510/525 and 426/511 are prepared for 503 without taking 415. Statistical computing to at least the level of DATASCI 306 and/or Python experience.
551 in place of 451. Students with a strong math background (say, MATH 217 and MATH 451) and good performance in 413/500, 425/510/525 and 426/511 are prepared for DATASCI/STATS 551 without taking DATASCI/STATS 451. Training in statistical computing should be to at least the level of DATASCI 306.
531. Students with a strong math background (say, MATH 217 and MATH 451) and good performance in 413/500, 425/510/525 and 426/511 are prepared for DATASCI/STATS 531. Training in statistical computing should be to at least the level of DATASCI 306.
