Merge pull request #20 from UBC-MDS/qnorm

added qnorm.py with its function specifications

src/pystats/qnorm.py

@@ -0,0 +1,46 @@
+def qnorm(p, mean=0, sd=1, lower_tail=True):
+    """
+    
+    Quantile (Inverse Cumulative Distribution Function) of the normal distribution.
+
+    Parameters
+    ----------
+    p: np.float64
+        The probability for which to find the quantile.
+
+    mean: np.float64, optional
+        The mean (average) of the normal distribution. Default is 0.
+        
+    std_dev: np.float64, optional
+        The standard deviation of the normal distribution. Default is 1.
+
+    lower_tail: bool, optional
+        If True, return the probability to the left of p in the normal distribution. 
+        If False, return the probability to the right of p in the normal distribution.
+        Default is True.
+        
+    Returns
+    -------
+    np.float64
+        Returns the value of the inverse cumulative density function (cdf) of the normal distribution 
+        given a certain random variable p, a population mean μ, and the population standard deviation σ.
+
+    Formula
+    -------
+    
+    If lower_tail=True:
+        Q(p; μ, σ) = μ + σ * sqrt(2) * erfinv(2p - 1)
+    
+    If lower_tail=False:
+        Q(p; μ, σ) = μ - σ * sqrt(2) * erfinv(2p - 1)
+
+    The quantile represents the value below which a given proportion of the distribution
+    falls. It is characterized by the mean (`μ`) and standard deviation (`σ`), determining
+    the center and spread of the distribution.
+
+    Example
+    -------
+    >>> qnorm(0.8413447460685429, mean=0, sd=1, lower_tail=True)
+    1.0
+
+    """