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  3. Introduction to Statistics in Python
  • 1

    Summary Statistics

    Gratuit

    Summary statistics gives you the tools you need to boil down massive datasets to reveal the highlights. In this chapter, you'll explore summary statistics including mean, median, and standard deviation, and learn how to accurately interpret them. You'll also develop your critical thinking skills, allowing you to choose the best summary statistics for your data.

  • 2

    Random Numbers and Probability

    In this chapter, you'll learn how to generate random samples and measure chance using probability. You'll work with real-world sales data to calculate the probability of a salesperson being successful. Finally, you’ll use the binomial distribution to model events with binary outcomes.

  • 3

    More Distributions and the Central Limit Theorem

    It’s time to explore one of the most important probability distributions in statistics, normal distribution. You’ll create histograms to plot normal distributions and gain an understanding of the central limit theorem, before expanding your knowledge of statistical functions by adding the Poisson, exponential, and t-distributions to your repertoire.

  • 4

    Correlation and Experimental Design

    In this chapter, you'll learn how to quantify the strength of a linear relationship between two variables, and explore how confounding variables can affect the relationship between two other variables. You'll also see how a study’s design can influence its results, change how the data should be analyzed, and potentially affect the reliability of your conclusions.

Initializing

Exercice

Simulating sales deals

Assume that Amir usually works on 3 deals per week, and overall, he wins 30% of deals he works on. Each deal has a binary outcome: it's either lost, or won, so you can model his sales deals with a binomial distribution. In this exercise, you'll help Amir simulate a year's worth of his deals so he can better understand his performance.

numpy is imported as np.

Instructions 1/4

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  • 1
    • Import binom from scipy.stats and set the random seed to 10.
  • 2
    • Simulate 1 deal worked on by Amir, who wins 30% of the deals he works on.
  • 3
    • Simulate a typical week of Amir's deals, or one week of 3 deals.
  • 4
    • Simulate a year's worth of Amir's deals, or 52 weeks of 3 deals each, and store in deals.
    • Print the mean number of deals he won per week.