Difference between revisions of "ISYE 3770"
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[[Category:Courses|^ISYE^ISYE]] |
[[Category:Courses|^ISYE^ISYE]] |
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| − | '''ISYE 3770: Statistics and Applications''' is a 3-credit course |
+ | '''ISYE 3770: Statistics and Applications''' is a 3-credit course in applied statistics and probability. It is cross-listed with [[MATH 3770]] and [[CEE 3770]]. |
| + | Note: some majors allow double-counting of ISYE 3770 for the Statistics requirement and as a non-major engineering elective. |
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| − | == Workload == |
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== Topic List == |
== Topic List == |
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* Linear regression and multiple linear regression |
* Linear regression and multiple linear regression |
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+ | == Workload == |
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| − | The official prerequisites are MATH 2401 or 2411 or 24X1 (Calculus III) and CS 1316 or equivalent. This list isn't comprehensive as I was able to take the course without either of those. I think MATH 2550 and CS 1331 are probably okay alternatives. |
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Latest revision as of 14:57, 12 May 2022
ISYE 3770: Statistics and Applications is a 3-credit course in applied statistics and probability. It is cross-listed with MATH 3770 and CEE 3770.
Note: some majors allow double-counting of ISYE 3770 for the Statistics requirement and as a non-major engineering elective.
Topic List[edit | edit source]
The textbook used is Applied Statistics and Probability for Engineers by Montgomery and Runger, especially chapters 2 through 13.
- Probability
- Discrete random variables
- Continuous random variables
- Binomial, geometric, negative binomial, hypergeometric, Poisson, continuous uniform, normal, and exponential distributions
- Joint probability distributions
- Descriptive statistics
- Sampling distributions and point estimation
- Confidence intervals
- Hypothesis testing
- Statistical inference for two samples
- Linear regression and multiple linear regression
Workload[edit | edit source]
Content is assessed through homework and assignments and exams. Use of statistical computer software such as Excel or R may be required in some homework assignments. ISYE 3770 is considered to be an easier class compared to equivalent math courses in probability and statistics.
