input: Write a python function to analyze the sentiment of a given text using NLTK's SentimentIntensityAnalyzer.
  assert analyze_sentiment("This movie was absolutely amazing!") == "Positive"
  assert analyze_sentiment("This movie was terrible!") == "Negative"
  assert analyze_sentiment("It was an okay movie.") == "Neutral"
output: def analyze_sentiment(text):
      from nltk.sentiment import SentimentIntensityAnalyzer
      sia = SentimentIntensityAnalyzer()
      scores = sia.polarity_scores(text)
      if scores['compound'] >= 0.05:
          return "Positive"
      elif scores['compound'] <= -0.05:
          return "Negative"
      else:
          return "Neutral"