[Term Entry] Data Science Data Distributions: Exponential Distribution

* Created the entry

* Update content/data-science/concepts/data-distributions/terms/exponential-distribution/exponential-distribution.md

Co-authored-by: Aditya Raj <41803857+raditya1117@users.noreply.github.com>

* Minor changes

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content/data-science/concepts/data-distributions/terms/exponential-distribution/exponential-distribution.md

@@ -0,0 +1,48 @@
+---
+Title: 'Exponential Distribution'
+Description: 'The exponential distribution is a probability distribution often used to model the time between events in a Poisson process.'
+Subjects:
+  - 'Data Science'
+  - 'Statistics'
+Tags:
+  - 'Data Distributions'
+  - 'Exponential'
+CatalogContent:
+  - 'learn-data-science'
+  - 'paths/data-science'
+---
+
+The **exponential distribution** models the time between independent events that occur at a fixed average rate. It is frequently used in reliability analysis, queuing theory, and survival analysis. The distribution is defined by a single parameter, the rate λ which determines how quickly events occur.
+
+The exponential distribution formula is given by:
+
+$$f(x|λ) = λ e^{-λ x}$$
+
+- `λ`: The rate parameter that represents the number of events per unit time.
+- `x`: A random variable that represents the time between events.
+
+## Example
+
+The example below demonstrates how to generate random samples from an exponential distribution using NumPy and visualize the results with a histogram using Matplotlib:
+
+```python
+import numpy as np
+import matplotlib.pyplot as plt
+
+# Set the rate parameter (lambda)
+rate = 1.5  # Events per unit time
+
+# Generate 1,000 random samples from the exponential distribution
+data = np.random.exponential(scale=1/rate, size=1000)
+
+# Plot the histogram of the generated data
+plt.hist(data, bins=30, density=True, alpha=0.6, color='teal', edgecolor='black')
+plt.title(f"Exponential Distribution (rate = {rate})")
+plt.xlabel("Time Between Events")
+plt.ylabel("Density")
+plt.show()
+```
+
+The above code produces the following output:
+
+![The output for the above example](https://raw.githubusercontent.com/Codecademy/docs/main/media/exponential-distribution.png)

documentation/tags.md

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 VR
 Vue
 Web3
+Exponential
 WebRTC
 Weight & Bias
 While