Math 4240: Probability
General Info
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Resources
Virtual Laboratories in Probability and Statistics by Kyle Siegrist
Lecture Notes
September 17
November 15
November 17
Homework: Starred problems will be graded.
Chapter 2: Due Wed Sept 1: 1, 2*, 4*, 5*, 7*, 8
Due Wed Sept 8: 11, 14, 15*, 18*, 21*, 22, 23, 27*, 29, 33*, 34, 35*, 36*, 41, 43*, 46, 47, 51*, 53*, 57, 58*, 68*, 69
Due Wed Sept 15: 71*, 73, 75*, 77*, 83, 84, 86, 89, 97, 99, 104*, 107*, 109, 114*, 115*, 119, 120*, 121*,
Due Mon Sept 20: 123*, 128*, 132*, 135*, 137 Solutions
Chapter 3: Due Fri Sept 24: 2, 4*, 6*, 10, 19, 23*, 27*, 29*, 32, 33* Solutions
Due Mon Oct 4: 40* 44, 48*, 51, 56*, 57*, 65*, 66*, 67*, 70*, 72*, 77, 80*, 85, 90*, 91*, 102*, 105*, 110, 122*, 130, 134*
Due Wed Oct 13: 147*, 148*, 150*, 151*, 153*, 159*, 160 Solutions
Chapter 4: Due Fri Oct 15: 9: 3*, 4*, 8*, 9*, 11, 15, 17*, 18 Solutions
Due Fri Oct 29: 21, 25*, 26*, 32*, 34*, 35*, 38*, 41*, 42*, 43, 44*, 45, 46, 50*, 55*, 57*, 81*, 82*, 89, 92*, 94*, 95*, 104*,
109*, 111*, 112* Solutions
Due Wed Nov 10: You don't have to use the tables to find normal probabilities. You may use your calculator. 58*, 59*, 60, 61, 62*, 71*, 75, 136*, 138*, 140*, 142*, 143*, 144, 145, 4.146*, 4.149*, 4.152* Partial Solutions (most were sent in email)
Chapter 5: Due Fri Nov 19: 7*, 9*, 11, 17*, 19*, 23*, 25*, 34*, 36*, 43, 45, 48*, 49*, 50*, 57*, 61, 64*, 71*, read section 5.6*, #s 75*, 77*, 79*, 81*
Exam Solutions/Review
Exam I will cover the work we've done so far through section 3.8 of the text.
Exam II will cover section 3.9, 4.1, 4.2, 4.3, 4.4, 4.5, 4.6, 4.8, 4.9, 4.10.
Exam II Review (fall 2010):
Be able to identify probability distributions (discrete and continuous) by their mgfs.
Know and be able to apply the defining properties of pdfs and cdfs to determine pdfs and cdfs.
Know the pdf is the derivative of the cdf, and the cdf is the integral of the pdf.
Be able to find means and variances of continuous random variables, as well as functions of continuous random variables.
Be able to identify, calculate probabilities, means, variances, moments for uniform, normal, exponential, and gamma random variables.
Be able to apply Chebyshev’s Theorem.
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