While simulating data, a distribution was observed, but the specific type of probability distribution was unknown. Your video provided the answer to this question. Thanks for your great video, you have gained a subscriber.
How can I find mean and variance of probability distribution using python? I have mentioned a problem below. Thanks in advance! The number of times I go to the gym in weekdays, are given below along with its associated probability: x = 0, 1, 2, 3, 4, 5 f(x) = 0.09, 0.15, 0.40, 0.25, 0.10, 0.01 Calculate the mean no. of workouts in a week. Also evaluate the variance involved in it.
How to use on real dataset,as an example how would I know if one of my columns follows geometric or Poisson distribution? Also we can't do geomtric,Poisson test on any columns,right?
Hello sir , please help me to find a solution of one of my question suppose x and y are random number uniformly distributed in the interval (0;1) what would be the distribution of z=x+y Please guide me how. To do this program .
Why does the plot for the uniform distribution not rise/fall to zero below and at the min/max values? I would have expected the values outside the range to be zero and then a near vertical rise/fall at min/max? Is that just interpolation of the plot?
It is just a quirk of the smoothing of the density plot function that makes it look like there is a little bit of density outside of the min and max. There are no values outside the min and max.
how would you do this Say you started a UA-cam channel about a year ago. You’ve done quite well so far and have collected some data. You want to know the probability of at least x visitors to your channel given some time period. The obvious choice in distributions is the Poisson distribution which depends only on one parameter, λ, which is the average number of occurrences per interval. We want to estimate this parameter using Maximum Likelihood Estimation. Simulate 100 visits to your youtube channel, assuming that they will a Poisson distribution with a mean of 10 visits per minute. Plot the arrival time vs visitor index.
You could generate 100 random exponentially distributed data points with lambda = 10, take the cumulative sum of those values to convert each arrival time into a vector of 100 successive arrivals and then plot them against the indices.
Hey, I can solve this problem using the formula longhand with Python. Do you know an easier way to accomplish this with scipy? The problem is: What is the probability that the world series will last 4 games? 5 games? 6 games? 7 games? Assume that the teams are evenly matched.
Not sure off the top of my head; for problems where I'm not sure how to set up the distributions to get an exact answer, I would generally just code up a simulation and run 100k trials or so to estimate the answer.
If you want random uniforms you can use the method shown in the video with scipy.stats or use the base python random module: import random random.random() # generate 1 random uniform
Nice 😊 Thank you for sharing Can you please provide coding with example for each distribution? Kindly guide me Or can you provide any source to study python for probability distribution please?
While simulating data, a distribution was observed, but the specific type of probability distribution was unknown. Your video provided the answer to this question. Thanks for your great video, you have gained a subscriber.
This is really helpful for beginners like me. Going through all courses and have learned most concepts needed for data analytics.
This is what I've been looking for. Thank you!!
Subscribed btw.
(16:42) 99% should represent the percentage of the data below 3, not above 3. Isn't it ?
Good call. That is correct
your videos are so helpful. if you add one or two real data analyst project to your videos, your package would be one of the best. thank you
This content is extremely helpful! Thank you for posting it.
Do you have any videos on how to fit data in python?
How can I find mean and variance of probability distribution using python? I have mentioned a problem below. Thanks in advance!
The number of times I go to the gym in weekdays, are given below along with its
associated probability:
x = 0, 1, 2, 3, 4, 5
f(x) = 0.09, 0.15, 0.40, 0.25, 0.10, 0.01
Calculate the mean no. of workouts in a week. Also evaluate the variance involved in
it.
How to use on real dataset,as an example how would I know if one of my columns follows geometric or Poisson distribution?
Also we can't do geomtric,Poisson test on any columns,right?
Thank you so much. This is very helpful.
Hello sir , please help me to find a solution of one of my question
suppose x and y are random number uniformly distributed in the interval (0;1) what would be the distribution of z=x+y
Please guide me how. To do this program .
Why does the plot for the uniform distribution not rise/fall to zero below and at the min/max values? I would have expected the values outside the range to be zero and then a near vertical rise/fall at min/max? Is that just interpolation of the plot?
It is just a quirk of the smoothing of the density plot function that makes it look like there is a little bit of density outside of the min and max. There are no values outside the min and max.
Great stuff as always, amazing amount of information in such a short amount of time and yet still very concise
Do you have a book?
Sucks that the Goat doesn’t make vids anymore :/ dude got me started in python & I can’t thank him enough🥲
16:20 not above 3sd but below 3sd
your videos are fantastic
Thanks!
THANK YOU
how would you do this
Say you started a UA-cam channel about a year ago. You’ve done quite well so far and have collected some data. You want to know the probability of at least x visitors to your channel given some time period. The obvious choice in distributions is the Poisson distribution which depends only on one parameter, λ, which is the average number of occurrences per interval. We want to estimate this parameter using Maximum Likelihood Estimation.
Simulate 100 visits to your youtube channel, assuming that they will a Poisson distribution with a mean of 10 visits per minute. Plot the arrival time vs visitor index.
You could generate 100 random exponentially distributed data points with lambda = 10, take the cumulative sum of those values to convert each arrival time into a vector of 100 successive arrivals and then plot them against the indices.
Hey, I can solve this problem using the formula longhand with Python. Do you know an easier way to accomplish this with scipy? The problem is: What is the probability that the world series will last 4 games? 5 games? 6 games? 7 games? Assume that the teams are evenly matched.
Not sure off the top of my head; for problems where I'm not sure how to set up the distributions to get an exact answer, I would generally just code up a simulation and run 100k trials or so to estimate the answer.
From which website are you teaching?
thank you
Great video
How to create function for uniform distribution in python ?
If you want random uniforms you can use the method shown in the video with scipy.stats or use the base python random module:
import random
random.random() # generate 1 random uniform
thanks
How to give the data manually and calculate cdf pdf
Like X and probability (X) will be given
Nice 😊
Thank you for sharing
Can you please provide coding with example for each distribution?
Kindly guide me
Or can you provide any source to study python for probability distribution please?
Merci (: