1. The way to calculate the variance of a certain set of data:
pts_mean = sum(nba_stats["pts"])/len(nba_stats['pts'])
point_variance = 0
for i in nba_stats['pts']:
difference = (i - pts_mean) ** 2
point_variance += difference
point_variance = point_variance / len(nba_stats['pts'])
2. Something to the power has the highest pirority, then mutiply and devide, the add and subsract.
3. Raise 11 to the fifth power. Assign the result to e.(11**5)
Take the fourth root of 10000. (10000**(1/4))
4. Use std() method to get the standard diviation:
std_dev = nba_stats["pf"].std()
5. To get the normal distribution:
from scipy.stats import norm
points_two = np.arange(-10,10,0.1) #setup the x value by distributing from 100 points from -10 to 10 evenly.
probabilities_two = norm.pdf(points_two,0,2) # get the normal distribution by using norm function
plt.plot(points,probabilities_two) # plot the points
plt.show()
6. In the normal distribution:
68% of the data is within 1 standard deviation of the mean, about 95% is within 2 standard deviations of the mean, and about 99% is within 3 standard deviations of the mean
7.
