Need help with my Statistics question – I’m studying for my class.
Think of some discrete random variable you observe on a regular basis. For example, it could be the (rounded) number of hours you sleep, how many gallons of gas are in your car when you get into it, how many boxes of cereal are in your house, how many days between grocery shopping, etc. (just make sure it takes only integer values). Try to list all of the possible values that this discrete random variable can take. If you can, collect some frequency data – give the relative frequency table and use this as an estimate of the probability distribution. Calculate the expected value and the standard deviation for this probability distribution. Interpret these parameters, and discuss whether they make sense based on your experience.
Week 4 Responses (100+ words, x2):
Look at your classmates’ distribution. Is there any well-known distribution that could be used to model their random phenomenon? Some well-known discrete distributions are: Uniform, Bernoulli, Binomial, Geometric, and Poisson (but there are others). Explain why this distribution might be appropriate. Post a picture of the discrete distribution and a histogram of the frequency data from the original post, and comment on what is similar and different. Are there any outliers that, if removed, would make the frequency data match the distribution really well?
RESPOND TO CLASSMATE:Rosemary DistributionDiscussion B
Working only two days a week as a result of the current pandemic, I am usually at the balcony observing the number of the days the pest control man comes to our community. For the sake of this assignment, I started monitoring the frequency at which the pest control man visits our community within a month. In other words, for my frequency I kept track of the days which he comes around. Per the question:
1. We have to calculate the expected value and the standard deviation for this probability distribution, interpret these parameter and discuss whether they make sense based on your experience.
2. Discrete random variable: Number of days the pest control man comes to my community in a month;
3. Possible value of the above random variation: 0, 1, 2, 3, 4…29, 30, 31.
| Number of Days | Mid Value | Frequency | Relative Frequency |
| 0-2 | 1 | 4 | 4/12=0.3333 |
| 3-5 | 4 | 5 | 5/12=0.4167 |
| 6-8 | 7 | 2 | 2/12=0.1667 |
| 9-11 | 10 | 1 | 1/12=0.0833 |
| Total | 12 | 1 |
With the probability distribution, I would calculate it by multiplying each mid value with the answer obtained from calculating the relative frequency which is the probability of the pest control man’s visitations in a given month.
So let mid value = (Xi) and Probability = (Pi)
| Mid Value | Probability | (Xi)(Pi) |
| 1 | 0.3333 | 0.3333*1 |
| 4 | 0.4167 | 0.1467*4 |
| 7 | 0.1667 | 0.1667*7 |
| 10 | 0.0833 | 0.0833*10 |
| Total | 1 | 4 |
Based on the table and the total attained, the expected value is 4 days in the month. Meanwhile, I had difficulties calculating the standard deviation which I believe should be in between 2 or 3 days out of the expected value of 4 days. Honestly, I do not know if my parameter makes sense having trouble calculating the standard deviation
.RESPOND TO Destinee Mills distribution.
When deciding what random variable I would use for this discussion in my daily life I came up with the number of hours I sleep. Being a mother of a 4 year old , part-time employee and nursing student the amount of hours I sleep throughout the seven day week vary. I have come up with the number of hours slept per day from Monday-Sunday. 7,5,6,5,6,7, 6.5 were the average amount of hours slept per day last week. The ascending order for the averages are as followed: 5,5,6,6,6.5,7,7.
Daily average: Frequency:
5 2
6 2
6.5 1
7 2
The expected value is : 5,5,6,6,6.5,7,7,
Daily average: Frequency: Relative: Cumulative Relative
5 2 2/7 (0.28) 0.28
6 2 2/7(0.28) 0.28
6.5 1 1/7(0.14) 0.14
7 2 2/7(0.28) 0.28
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