Data collection and presentation, descriptive statistics. Probability distributions, sampling distributions and the central limit theorem. Point estimation, confidence intervals and hypothesis testing. Correlation and regression analysis. ANOVA. Goodness of fit and contingency table. Prerequisite: Mathematics 30-1 or 30-2. Notes: (1) Credit can be obtained in at most one of STAT 151, STAT 161, and STAT 235. (2) This course may not be taken for credit if credit has been obtained in STAT 222, STAT 266, STAT 276, KIN 109, PEDS 109, PSYCH 211, PTHER 352, SCI 151 or SOC 210.
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LECTURE P1
(84418) |
210 |
2026-01-05 - 2026-04-10 (MWF)
08:00 - 08:50
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LECTURE Q1
(82814) |
210 |
2026-01-05 - 2026-04-10 (MWF)
09:00 - 09:50
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LECTURE R1
(82710) |
210 |
2026-01-05 - 2026-04-10 (MWF)
12:00 - 12:50
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LECTURE S1
(83169) |
210 |
2026-01-05 - 2026-04-10 (MWF)
13:00 - 13:50
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LECTURE T1
(82709) |
200 |
2026-01-05 - 2026-04-10 (MWF)
14:00 - 14:50
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LECTURE U1
(83170) |
250 |
2026-01-05 - 2026-04-10 (TR)
14:00 - 15:20
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LECTURE V1
(87094) |
175 |
2026-01-05 - 2026-04-10 (MWF)
10:00 - 10:50
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