Continuous Probability Distribution


Comparison between discrete and continuous distributions.

Exhibit 33.14 Comparison between discrete and continuous distributions.

A comparison between discrete and continuous probability distributions is given in Exhibit 33.14. The probability distribution of a continuous random variable, X, is described by its probability density function (pdf), f(x).

$$Mean \,μ = \int_{-∞}^∞ x f(x)dx$$ $$Variance \,σ = \int_{-∞}^∞ (x-μ)^2 f(x)dx$$

For a given time, t, the cumulative distribution function (cdf) F(t) of a continuous random variable, X, is defined by:

$$F(t)=P(X≤t)=\int_{-∞}^t f(x)dx$$ $$F(-∞)=0,\,F(∞)=1 $$

Previous     Next

Use the Search Bar to find content on MarketingMind.







Marketing Analytics Workshop

Marketing Analytics Workshop

In an analytics-driven business environment, this analytics-centred consumer marketing workshop is tailored to the needs of consumer analysts, marketing researchers, brand managers, category managers and seasoned marketing and retailing professionals.


Digital Marketing Workshop

Digital Marketing Workshop

Unlock the Power of Digital Marketing: Join us for an immersive online experience designed to empower you with the skills and knowledge needed to excel in the dynamic world of digital marketing. In just three days, you will transform into a proficient digital marketer, equipped to craft and implement successful online strategies.