Variantie en standaardafwijking

Variantie en standaardafwijking zijn twee van de meest gebruikte manieren om de spreiding van een variabele te meten. In deze oefening ga je ze berekenen. Spreiding is belangrijk omdat het helpt je verwachtingen bij te sturen. Stel dat een verkoper gemiddeld 20 producten per dag verkoopt, maar een standaardafwijking heeft van 10 producten. Dan zullen er waarschijnlijk dagen zijn waarop hij 40 producten verkoopt, maar ook dagen met maar één of twee verkopen. Zulke informatie is waardevol, zeker als je voorspellingen wilt doen.

De bibliotheken dplyr en ggplot2 zijn geladen en food_consumption is beschikbaar.

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Inleiding tot statistiek in R

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Inleiding tot statistiek in R

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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.

Exercise 1: Wat is statistiek?Exercise 2: Beschrijvende en inferentiële statistiek Exercise 3: Classificatie van datatypes Exercise 4: Maten van centrum Exercise 5: Gemiddelde en mediaan Exercise 6: Gemiddelde vs. mediaan Exercise 7: Spreidingsmaten Exercise 8: Variantie en standaardafwijking

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Exercise 9: Kwartielen, kwantielen en kwintielen Exercise 10: Uitschieters vinden met IQR

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.

Exercise 1: What are the chances?Exercise 2: With or without replacement?Exercise 3: Calculating probabilities Exercise 4: Sampling deals Exercise 5: Discrete distributions Exercise 6: Creating a probability distribution Exercise 7: Identifying distributions Exercise 8: Expected value vs. sample mean Exercise 9: Continuous distributions Exercise 10: Which distribution?Exercise 11: Data back-ups Exercise 12: Simulating wait times Exercise 13: The binomial distribution Exercise 14: Simulating sales deals Exercise 15: Calculating binomial probabilities Exercise 16: How many sales will be won?

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.

Exercise 1: The normal distribution Exercise 2: Distribution of Amir's sales Exercise 3: Probabilities from the normal distribution Exercise 4: Simulating sales under new market conditions Exercise 5: Which market is better?Exercise 6: The central limit theorem Exercise 7: Visualizing sampling distributions Exercise 8: The CLT in action Exercise 9: The mean of means Exercise 10: The Poisson distribution Exercise 11: Identifying lambda Exercise 12: Tracking lead responses Exercise 13: More probability distributions Exercise 14: Too many distributions Exercise 15: Modeling time between leads Exercise 16: The t-distribution

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.

Exercise 1: Correlation Exercise 2: Guess the correlation Exercise 3: Relationships between variables Exercise 4: Correlation caveats Exercise 5: What can't correlation measure?Exercise 6: Transforming variables Exercise 7: Does sugar improve happiness?Exercise 8: Confounders Exercise 9: Design of experiments Exercise 10: Study types Exercise 11: Longitudinal vs. cross-sectional studies Exercise 12: Congratulations!