- #1
stucano
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Hi guys,
I'm having trouble with this book - "Introduction to Probability and Statistics for Engineers and Scientists" by Sheldon M. Ross. The explanations are very short and often lack necessary details, the examples are very hard and apparently some full of errors. I just can't study from it and it's becoming incredibly frustrating.
I'm mostly doing self-study with video lectures when needed but I need a good book for this. My course's curriculum for the probability part is Chapters 3, 4 and 5. Here are the details:
Chapter 3 - Elements of probability
* Conditional probability
* Bayes' Formula
* Independent events
Chapter 4 - Random variables and Expectation
* Random variables, types
* Jointly distributed random vars
* Expectations
* Properties of expected value
* Variance, covariance and variance of sums of rand vars
* Moment generating func
* Chebyshev's inequality and the weak law of large numbers
Chapter 5 - Special random variables
* Bernoulli random variables
* Poisson random variable
* Hypergeometric random variable
* Uniform random variable
* Normal random variable
* Exponential random variable
* Gamma distribution
* Distributions arising from the normal
- Chi-Square, t-Distribution, F-distribution
* Logistics distribution
We cover probability first then statistics. Can anyone please recommend a good substitute that has all the above material? Anything would be useful, course notes, book(s), other materials even if they are just parts of the above chapters.
I'm having trouble with this book - "Introduction to Probability and Statistics for Engineers and Scientists" by Sheldon M. Ross. The explanations are very short and often lack necessary details, the examples are very hard and apparently some full of errors. I just can't study from it and it's becoming incredibly frustrating.
I'm mostly doing self-study with video lectures when needed but I need a good book for this. My course's curriculum for the probability part is Chapters 3, 4 and 5. Here are the details:
Chapter 3 - Elements of probability
* Conditional probability
* Bayes' Formula
* Independent events
Chapter 4 - Random variables and Expectation
* Random variables, types
* Jointly distributed random vars
* Expectations
* Properties of expected value
* Variance, covariance and variance of sums of rand vars
* Moment generating func
* Chebyshev's inequality and the weak law of large numbers
Chapter 5 - Special random variables
* Bernoulli random variables
* Poisson random variable
* Hypergeometric random variable
* Uniform random variable
* Normal random variable
* Exponential random variable
* Gamma distribution
* Distributions arising from the normal
- Chi-Square, t-Distribution, F-distribution
* Logistics distribution
We cover probability first then statistics. Can anyone please recommend a good substitute that has all the above material? Anything would be useful, course notes, book(s), other materials even if they are just parts of the above chapters.