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Read the question carefully and dont miss up any key word like anerage,mean and standard deviation. Identify the type of distribution. Use the suitable formula to solve the problem.

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Strategy is to identify is it is binomial or Poisson distribution. Then find out if its discrete or continuous. Next find the value of n. Identify from which chapter the question is related to. Normal distribution the key words may not be in the problem statement but the question too.

Understand the question. Do not leave it empty. Use the formula given and memorise the ones not provided

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NURSYAZWANI BT AHMAD SABRI 262102

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IZZAH FARHAH SALEHHUDDIN  265133

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need confirm the statement that question about, and then differentiate what question need

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Nabila Arifah Binti Abdul Samad
263668

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261305

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Mohamad Farid (263877)

Distribution of random variables

Discerete - Binomial
Fixed number of n trials, each trials has 2 outcomes ( success or failure), outcomes are independent, same probability of success for each trials.

Poisson
Average number of occurences per unit time or space. The occurrences are random and independent.

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NUR ALYYA SYAHIRA BINTI AHMAD ROSMIN 263734

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NUR ALYYA SYAHIRA BINTI AHMAD ROSMIN 263734

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Based on the 3 samples of the past year questions about questions that related to Chap 5, I can conclude that the question structure are quite challenging as we need to identify wether it is a discrete or continous distributions before we start to answer it. But as I had been practised the questions in the class many times, I can easily identify the types of question and of course can continue to calculate the formula and answering the questions given. Practise to answering the questions together with lecturer do help making these types of question easy to do.

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Based on 3 samples of past year questions about question related to Chapter 5, i can conclude that :-

1) we should identify the terms that is used in the questions to know whether it is discrete or continuous.
2) then, highlight the important point.
3) for example, the percentage, the number of sample and time.
4) then, we can solve the question using the right formula.

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263527

My conclusion is the Binomial have two outcomes. The  probability of success is known and constant over all trials. Second, Poisson Distribution is useful when n is large and p is small and when the independent variables occur over a period of time.

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Strategies:
A) Descrete distribution have 2:
1. Binomial
-have 2 outcomes
- p+q=1 (success or failure)
- have 'n'
- between 0 and 1

2. Poisson
- area + volume (space)
- time (period)
- keyword: average

B) Continuous distribution
Normal
- use value of Z
- mean & standard deviation
- total Z is 3.9

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Binomial
It is descrete bc the number is stated.
2 outcome -independent
- p+q=1
It can be success + failure
Basically it can be detect by “n” or “%” that stated in the question

Poisson
Same goes to binomial it is descrete
Occurance(mean) are random + midpoint
Area + valume (space)
It can be recognise by average that stated in question

Normal
It is continuous bc of decimal
It already stated in the question

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1. read and understand the question
2. find the pattern (binomial and poisson)
3. find out is it discrete or continuous
4. find the value of n

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MUHAMAD AFIF HAZWAN BIN ROSS MASWADEE

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I can conclude that the most important things is we need to understand the questions given clearly and then determine what the distribution that we need to used (Binomial or Poisson distribution). The final steps is we just put the number in the formula given.

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LAILA HAZIRAH BINTI HASNAN EFFENDI

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THIVYA SHALINI 265012

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- read and understand the question.
- find out is it binomial or poisson
- find out is it discrete or continuos

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nur izzati sorfina binti johari 264492

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Normal distribution:

1.The mean, mode and median are all equal
2.The curve is symmetric at the center (i.e. around the mean, μ).
3.Exactly half of the values are to the left of center and exactly half the values are to the right.
4.The total area under the curve is 1.

Binomial Distribution:

1. Each trial has a binary outcome (One of the two outcomes is labeled a ‘success’)

2. The probability of success is known and constant over all trials

3. The number of trials is specified

4. The trials are independent. That is, the outcome from one trial doesn’t affect the outcome of successive trials

Poisson distribution

The horizontal axis is the index X. The function is defined only at integer values of X. The connecting lines are only guides for the eye and do not indicate continuity. Notice that as λ increases the distribution begins to resemble a normal distribution.

If λ is 10 or greater, the normal distribution is a reasonable approximation to the Poisson distribution

The mean and variance for a Poisson distribution are the same and are both equal to λ

The standard deviation of the Poisson distribution is the square root of λ

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264629

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Once read the question ~

1. Find the pattern (binomial/poisson)
2. Find out is it “discrete or continuous”
3. Find the value of n
4. Highlight all the keywords
5. Identify the questions from which chapter in sylybus
6. Normal distribution
- sometimes the keywords not only in the problem statement, but also in the question. Be alert.
7. Look over the event and the variable

-understand the questions given
-dont blank the answer
-give the hint
-remember the formula

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Conclusion for chapter 5 (264937)
Conclusion. The binomial distribution is a discrete probability distribution used when there are only two possible outcomes for a random variable: success and failure. Success and failure are mutually exclusive; they cannot occur at the same time. The binomial distribution assumes a finite number of trials, n.

If μ is the average number of successes occurring in a given time interval or region in the Poisson distribution, then the mean and the variance of the Poisson distribution are both equal to μ. Note: In a Poisson distribution, only one parameter, μ is needed to determine the probability of an event.

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Fatin Fathihah binti Saiful Rizal

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Get access to files anywhere through secure cloud storage and file backup for your photos, videos, files and more with Google Drive.

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My conclution is the Binomial and Poisson distributions are similar, but they are different. Also, the fact that they are both discrete does not mean that they are the same. The Geometric distribution and one form of the Uniform distribution are also discrete, but they are very different from both the Binomial and Poisson distributions.

The difference between the two is that while both measure the number of certain random events (or "successes") within a certain frame, the Binomial is based on discrete events, while the Poisson is based on continuous events. That is, with a binomial distribution you have a certain number, nn, of "attempts," each of which has probability of success pp. With a Poisson distribution, you essentially have infinite attempts, with infinitesimal chance of success. That is, given a Binomial distribution with some n,pn,p, if you let n→∞n→∞ and p→0p→0 in such a way that np→λnp→λ, then that distribution approaches a Poisson distribution with parameter λλ.

Because of this limiting effect, Poisson distributions are used to model occurences of events that could happen a very large number of times, but happen rarely. That is, they are used in situations that would be more properly represented by a Binomial distribution with a very large nn and small pp, especially when the exact values of nn and ppare unknown. (Historically, the number of wrongful criminal convictions in a country)

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Conclusion of me was to analysis the question are different types of probability distributions, like the binomial distribution, normal distribution and Poisson distribution. All of these distributions can be classified as either a continuous or a discrete probability distribution.
A discrete probability distribution is made up of discrete variables. Specifically, if a random variable is discrete, then it will have a discrete probability distribution
• A probability distribution tells you what the probability of an event happening is. Probability distributions can show simple events, like tossing a coin or picking a card. They can also show much more complex events, like the probability of a certain drug successfully treating cancer.

• A binomial distribution can be thought of as simply the probability of a SUCCESS or FAILURE outcome in an experiment or survey that is repeated multiple times. The binomial is a type of distribution that has two possible outcomes (the prefix “bi” means two, or twice). For example, a coin toss has only two possible outcomes: heads or tails and taking a test could have two possible outcomes: pass or fail.

The binomial distribution formula is:

b(x; n, P) = nCx * Px * (1 – P)n – x

Where:
b = binomial probability
x = total number of “successes” (pass or fail, heads or tails etc.)
P = probability of a success on an individual trial
n = number of trials

• A normal distribution, sometimes called the bell curve, is a distribution that occurs naturally in many situations. For example, the bell curve is seen in tests like the SAT and GRE. The bulk of students will score the average (C), while smaller numbers of students will score a B or D. An even smaller percentage of students score an F or an A. This creates a distribution that resembles a bell (hence the nickname). The bell curve is symmetrical. Half of the data will fall to the left of the mean; half will fall to the right.

• A Poisson distribution is a tool that helps to predict the probability of certain events from happening when you know how often the event has occurred. It gives us the probability of a given number of events happening in a fixed interval of time.

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https://drive.google.com/file/d/1xXM8oJP8TI1n8IimjWXSq7wsVJMEEppr/view?usp=drivesdk

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As a conclusion, we have to identify whether each of the sample is binomial or poisson distribution based on their characteristics.Therefore, we need to read the questions properly.We also must do more additional past years questions to gain more knowledge on how to answer any questions related to this chapter 5.

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My conclusion is:
I need to confirm is parameter to determine is Poisson or Binomial and Normal. And proceed to determinent that questions did or didn't include "n" after confirm it given 2 parameter.