Already have an account? Get multiple benefits of using own account!
Login in your account..!
Remember me
Don't have an account? Create your account in less than a minutes,
Forgot password? how can I recover my password now!
Enter right registered email to receive password!
Binomial Distribution
Binomial distribution was discovered by swiss mathematician James Bernonulli, so this distribution is called as Bernoulli distribution also, this is a discrete frequency distribution.
Assumptions of a binomial Distribution
1. The random experiment is performed repeatedly with a fixed and finite number of trials. N is denoted by number of trials.
2. There are two mutually exclusive possible outcomes on each trial which are known as success and failure success is denoted by whereas failure is denoted by q, and p+q = 1 or q=1-p1.
3. The outcomes of any given trial does not affect the outcomes on subsequent trials means the trials are independent.
4. The probability of success and failure (p&q) remains constant from trial to trial. If in any distribution the p& q does not remain constant that distribution cannot be a binomial distribution, For example the probability of getting head must remain the same in each toss i.e. ½ similarly the probability of drawing 4 balls from a bag containing 6 red and 10 white balls does not change in successive draws with replacement, hence it will be called as binomial distribution .But in contrary to this, if balls are not replaced after each trail then it will not be a binomial distribution.
5. If all above assumptions are satisfied , the probability of exactly r successes in n trials is given by
6. P(n=r)=n crprqn-r
The Null Hypothesis - H0: The random errors will be normally distributed The Alternative Hypothesis - H1: The random errors are not normally distributed Reject H0: when P-v
1. For each of the following variables: major, graduate GPA, and height: a. Determine whether the variable is categorical or numerical. b. If the variable is numerical, deter
Multivariate analysis of variance (MANOVA) is a technique to assess group differences across multiple metric dependent variables simultaneously, based on a set of categorical (non-
case study in heat power engineering
how can i use continuous frailty in multi state models?
b. A paper mill produces two grades of paper viz., X and Y. Because of raw material restrictions, it cannot produce more than 400 tons of grade X paper and 300 tons of grade Y
what is non linear modl
This box plot displays the diversity wfood; the data ranges from 0.05710 being the minimum value and 0.78900 being the maximum value. The box plot is slightly positively skewed at
X 110 120 130 120 140 135 155 160 165 155 Y 12 18 20 15 25 30 35 20 25 10
Review the Learning Resources and the media programs related to t tests. For additional support, review the Skill Builder: Research Design and Statistical Design and the Skill Buil
Get guaranteed satisfaction & time on delivery in every assignment order you paid with us! We ensure premium quality solution document along with free turntin report!
whatsapp: +91-977-207-8620
Phone: +91-977-207-8620
Email: [email protected]
All rights reserved! Copyrights ©2019-2020 ExpertsMind IT Educational Pvt Ltd