Median, mode, normal distribution

In summary, the conversation discusses a digital communication channel where the number of bits received in error can be modeled by a binomial random variable with a bit error rate of 1×〖10〗^(−5). The question is about the probability of having more than 150 errors occur out of 16 million transmitted bits, as well as finding the median and mode of the distribution. The person asking for help is prompted for their current understanding of the binomial distribution and how to handle large numbers of samples.
  • #1
wajeehayas
2
0
In a digital communication channel, assume that the number of bits received in error can be modeled by a binomial random variable, and assumed that a bit is received in error is 1×〖10〗^(−5) . if 16 million bits are transmitted,
What is the probability that more than 150 errors occur?
Find the median and mode of the distribution.
help needed to solve this :)
 
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  • #2
wajeehayas said:
In a digital communication channel, assume that the number of bits received in error can be modeled by a binomial random variable, and assumed that a bit is received in error is 1×〖10〗^(−5) . if 16 million bits are transmitted,
What is the probability that more than 150 errors occur?
Find the median and mode of the distribution.
help needed to solve this :)

Hi wajeehayas!

What have you tried so far? What do you know about the binomial distribution? Here we have a large number of samples. Have you read or heard about how we can handle situations like that?
 

FAQ: Median, mode, normal distribution

What is median?

Median is a measure of central tendency that represents the middle value in a dataset when arranged in ascending or descending order. It is not affected by extreme values and is often used with skewed or non-normal data.

What is mode?

Mode is a measure of central tendency that represents the most frequently occurring value in a dataset. It is useful for representing categorical or discrete data, but may not be a good representation of continuous data.

What is normal distribution?

Normal distribution, also known as Gaussian distribution, is a symmetric probability distribution that can be described by its mean and standard deviation. It is commonly seen in nature and used in statistical analysis due to its many desirable properties.

How are median and mode different?

Median and mode are both measures of central tendency, but they represent different aspects of a dataset. While median represents the middle value, mode represents the most frequent value. Median is not affected by extreme values, but mode is. Additionally, median can be calculated for both numerical and ordinal data, while mode is typically used for categorical data.

When should normal distribution be used?

Normal distribution should be used when analyzing continuous data that has a symmetrical distribution. It is also appropriate when the data is unskewed or has a bell-shaped curve. However, it is important to note that not all data follows a normal distribution and other distributions may be more appropriate for certain datasets.

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