- #1
freedominator
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how are cdf and pdf related in statistics?
please help i have a test tomorrow
please help i have a test tomorrow
freedominator said:ok i think i got it
cumulative distribution function is the integral from 0 to k of a probability distribution function of k
thats why the p(k) =F(k)-F(k-1)
jwatts said:false P(X=k) for any density function is 0.
CDF stands for cumulative distribution function, which is a function that maps the probability of a random variable being less than or equal to a certain value. PDF stands for probability density function, which is a function that describes the probability of a random variable taking on a certain value.
The main difference between CDF and PDF is that CDF shows the probability of a random variable being less than or equal to a certain value, while PDF shows the probability of a random variable taking on a specific value. CDF is a cumulative function, while PDF is a probability function.
CDF and PDF are important concepts in statistics as they help in understanding the behavior and distribution of random variables. They are used to calculate probabilities, make predictions, and analyze data in various fields such as finance, economics, and engineering.
CDF and PDF are related through integration. CDF is the integral of PDF, and PDF is the derivative of CDF. In other words, the area under the PDF curve gives the CDF value, and the slope of the CDF curve gives the PDF value.
CDF and PDF can be visualized through graphs or plots. A CDF graph is a curve that starts at 0 and ends at 1, while a PDF graph is a curve that shows the probability density at different values of a random variable. These visualizations help in understanding the distribution and characteristics of a random variable.