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CHAPTER 1: Exercise 1

type: NormalExercise
lang: python
xp: 100
skills: 1
key: 7942f6cb9a

@hint

@instructions

@pre_exercise_code

import numpy as np
import scipy.stats as stats

@sample_code

@solution

# leave blank for now

@sct

# SCT written with pythonwhat: https://github.com/datacamp/pythonwhat/wiki

success_msg("Great work!")

Testing Proportions

type: PureMultipleChoiceExercise
key: b9a01998c7
xp: 50
skills: 2

Which question(s) cannot be answered using hypothesis testing for a proportion?

@possible_answers

  • Do the complaints coming from Manhattan constitute more than 50% of the entire NYC complaints?
  • Are there more than 50 percent of Americans who self-identify as liberal?
  • Is the proportion of babies born male different from 50 percent?
  • [Is the mean number of NYC complaints coming from Manhattan more than 100 per week?]

@hint

@feedback

CHAPTER 1: Exercise 2

type: NormalExercise
key: 1b8445f214
lang: python
xp: 100
skills: 2

@instructions

Type I and Type II errors. typeI_typeII_plotter() function plots the NULL and alternative distributions, and highlights the Type I and Type II errors.

@hint

@pre_exercise_code


import numpy as np
from scipy.stats import norm
import matplotlib.pyplot as plt

def typeI_typeII_plotter():
    plt.figure(figsize=(12,10))
    range = np.arange(-4, 4, 0.001)
    plt.plot(range, norm.pdf(range, 0, 1))
    range = np.arange(-4, 10, 0.001)
    plt.plot(range, norm.pdf(range, 3, 2))

    plt.fill_between(x=np.arange(-4,-2,0.01), y1= norm.pdf(np.arange(-4,-2,0.01)), facecolor='red', alpha=0.35)
    plt.fill_between(x=np.arange(-2,2,0.01), y1= norm.pdf(np.arange(-2,2,0.01)), facecolor='white', alpha=0.35)
    plt.fill_between(x=np.arange(2,4,0.01), y1= norm.pdf(np.arange(2,4,0.01)), facecolor='red', alpha=0.5)

    plt.fill_between(x=np.arange(-4,-2,0.01), y1= norm.pdf(np.arange(-4,-2,0.01),loc=3, scale=2), facecolor='white', alpha=0.35)
    plt.fill_between(x=np.arange(-2,2,0.01), y1= norm.pdf(np.arange(-2,2,0.01),loc=3, scale=2),facecolor='blue', alpha=0.35)
    plt.fill_between(x=np.arange(2,10,0.01), y1= norm.pdf(np.arange(2,10,0.01),loc=3, scale=2), facecolor='white', alpha=0.35)

    plt.text(x=-1.2, y=0.15, s= "Null Hypothesis", fontsize=6)
    plt.text(x=2.5, y=0.13, s= "Alternative", fontsize=6)
    plt.text(x=2.1, y=0.01, s= "Type 1 Error", fontsize=6)
    plt.text(x=-3.2, y=0.01, s= "Type 1 Error", fontsize=6)
    plt.text(x=0, y=0.02, s= "Type 2 Error", fontsize=6)
    
    plt.show()

@sample_code

typeI_typeII_plotter()

@solution

@sct


success_msg("Great work!")