Determine Whether Or Not The Function Is A Probability Density Function Over The Given Interval. 3 F(x)

Determine Whether Or Not The Function Is A Probability Density Function Over The Given Interval. 3 F(x)

When analyzing whether a function qualifies as a probability density function (PDF), it is essential to verify specific criteria that define the properties of PDFs in probability theory. The function in question, denoted as 3F(x), suggests a scaled version of some original function F(x). To ascertain if 3F(x) is a valid PDF over a given interval, one must examine its properties carefully. This involves ensuring that the function is non-negative over its domain and that the total integral over the specified interval equals 1. This article will guide you through the process of determining whether 3F(x) meets these criteria, discussing the necessary steps, mathematical conditions, and implications involved in the verification process.

Understanding Probability Density Functions (PDFs)

Definition and Properties of a PDF

A probability density function (PDF) is a fundamental concept in probability and statistics used to describe the likelihood of a continuous random variable taking on a particular value within a given range. Unlike discrete probability distributions, which assign probabilities to specific points, PDFs define the density of probability across a continuum.

The key properties of a PDF, f(x), are:

    • Non-negativity: f(x) ≥ 0 for all x in the domain.
  • Normalization: The total area under the curve of f(x) over its domain is 1, i.e.,
    ab f(x) dx = 1, where [a, b] is the interval of support.

Any function satisfying these properties can be considered a valid PDF. The second property ensures that the total probability across the entire domain sums to 1, aligning with the fundamental axioms of probability.

Implications of Scaling a PDF by a Constant

Scaling a PDF by a constant factor alters its total area. For example, multiplying a function F(x) by 3 results in a new function 3F(x). Whether this new function remains a valid PDF depends on whether the scaled area still sums to 1 over the specified interval.

If F(x) is a PDF, then:


  • ab F(x) dx = 1

  • The scaled function, 3F(x), will have an integral:


ab 3F(x) dx = 3 ∫ab F(x) dx = 3 × 1 = 3

which violates the normalization condition for a PDF. Therefore, unless the scaling factor is 1, the resulting function generally does not qualify as a PDF unless additional normalization is performed.

Step-by-Step Procedure to Verify Whether 3F(x) is a PDF

1. Identify the Support Interval

Before performing any calculations, determine the interval over which the function is defined. This is crucial because the properties of the function are only relevant within its support.


  • Check the problem statement or given data for the domain of F(x).

  • Note any restrictions or discontinuities that may influence the integral.


2. Verify Non-Negativity of 3F(x)

Since a PDF must be non-negative over its support:


  • Check the original function F(x): Is F(x) ≥ 0 for all x in the interval?

  • Determine the sign of 3F(x): Multiplying by 3 does not change the sign; if F(x) ≥ 0, then 3F(x) ≥ 0.


If F(x) takes negative values at any point in the interval, then 3F(x) will also be negative there, disqualifying it as a PDF.

3. Calculate the Integral of 3F(x) Over the Support

The core criterion involves the total integral:


  • Compute ab 3F(x) dx

  • Use the properties of integrals:


ab 3F(x) dx = 3 ∫ab F(x) dx

  • Evaluate this integral either analytically or numerically based on the form of F(x).


4. Check for Normalization



  • If ab 3F(x) dx = 1, then 3F(x) satisfies the normalization condition.

  • If the integral is greater than or less than 1, then 3F(x) does not qualify as a PDF in its current form.


Note: Since the integral of F(x) over the support is generally fixed (for example, if F(x) is a PDF), multiplying by 3 typically results in the integral being 3, which exceeds 1. Therefore, unless F(x) has an integral of 1/3 over its support, 3F(x) will not be a valid PDF without normalization.

Interpreting the Results and Additional Considerations

Case 1: F(x) is a Valid PDF and the integral of F(x) over its support is 1

  • The integral of 3F(x) over the same support is 3.
  • Therefore, 3F(x) is not a valid PDF because it does not satisfy the normalization condition.
  • Solution: Normalize 3F(x) by dividing by 3:
g(x) = (3F(x)) / 3 = F(x) (which is the original PDF).
  • Alternatively, consider scaling F(x) with a factor such that the total area is 1.

Case 2: F(x) is not a PDF, or its integral over the support is not 1

  • The integral of 3F(x) might be less than 1, equal to 1, or greater than 1.
  • If the integral is less than 1: 3F(x) is not a PDF unless scaled appropriately.
  • If the integral is greater than 1: same applies; normalization is necessary.

Implications of Scaling and Normalization

  • The act of multiplying by 3 is a simple scaling, but for a function to qualify as a PDF, the total area must be exactly 1.
  • If you desire to create a valid PDF from 3F(x), you must normalize by dividing by the total integral:
fnormalized(x) = (3F(x)) / ∫ab 3F(x) dx
  • This normalization ensures the total area under the curve is 1.

Practical Examples and Applications

Example 1: F(x) = (1/2) over [0, 2]

Suppose F(x) = (1/2) for x in [0, 2], zero elsewhere.


  • F(x) is a valid PDF because:

  • Non-negative over [0, 2].

  • Total area: ∫02 (1/2) dx = (1/2) × 2 = 1.

  • Now, consider 3F(x):

  • Integral over [0, 2]:


02 3F(x) dx = 3 × (1/2) × 2 = 3 × 1 = 3.

  • Since the total area is 3, 3F(x) is not a PDF unless scaled down.

  • To normalize:


g(x) = (3F(x)) / 3 = F(x).

  • Thus, the original F(x) is a valid PDF, but 3F(x) is not unless further normalization is applied.


Application: This example illustrates why scaling a PDF by a constant other than 1 generally invalidates it as a PDF unless normalized.

Example 2: F(x) = x/3 over [0, 3]

  • Calculate integral:
03 (x/3) dx = (1/3) × (x2/2) |03 = (1/3) × (9/2) = (1/3) × 4.5 = 1.5.
  • Since the integral is 1.5, F(x) is not a valid PDF, but scaled appropriately:
F(x) / 1.5 would be a valid PDF over [0, 3].
  • Now, consider 3F(x):
03 3F

Frequently Asked Questions

What are the key criteria to determine if a function F(x) is a probability density function over a given interval?
The function must be non-negative over the interval and the total area under the curve must equal 1.
How do you verify if the integral of F(x) over its interval equals 1?
Calculate the definite integral of F(x) over the interval and check if the result is exactly 1.
Can a function be a probability density function if it takes negative values within its interval?
No, a probability density function must be non-negative everywhere in its domain.
What is the significance of the total integral of F(x) being greater than or less than 1?
If the integral is greater than 1, it cannot be a probability density function; if less than 1, it also does not satisfy the total probability condition.
If F(x) is given as 3x over the interval [0,1], how do you determine if it is a valid probability density function?
Integrate 3x from 0 to 1, which gives 1.5, and since it's not equal to 1, F(x) is not a valid probability density function over [0,1].
What adjustments can be made to a function that is proportional to a probability density function but does not integrate to 1?
Normalize the function by dividing it by its total integral over the interval to ensure the area under the curve equals 1.
How does the interval over which F(x) is defined affect its qualification as a probability density function?
The interval defines the domain where the function must be non-negative and integrate to 1; changing the interval can affect these conditions.
What role does the normalization constant play in determining if a function is a probability density function?
The normalization constant ensures that the total area under the function over the interval equals 1, making it a valid probability density function.
If F(x) = 3F(x) over the interval [a, b], how do you verify if it is a probability density function?
Calculate the integral of 3F(x) over [a, b]; if the integral equals 1, then it is a valid probability density function.