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Probability & Statistics courses

Probability and statistics courses explore mathematical concepts for analyzing random events and interpreting data through models and inference. Use tools such as Python, R, Excel and Google Sheets to apply your theoretical knowledge in statistics.

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Recommended for Probability & Statistics beginners

Build your Probability & Statistics skills with interactive courses, curated by real-world experts

Cursus

Inleiding tot statistiek in R

GemiddeldVaardigheidsniveau
4 uur
5K

Leerpad

Statisticus in R

52 uur
969
Een statisticus verzamelt en analyseert gegevens en helpt bedrijven om kwantitatieve gegevens te begrijpen, zoals trends te herkennen en voorspellingen te doen.

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Cursus

Enquètegegevens analyseren in Python

GemiddeldVaardigheidsniveau
4 uur
111
Leer hoe je enquêtegegevens kunt analyseren met Python en ontdek wanneer het handig is om statistische tools te gebruiken die beschrijvend en inferentieel zijn.

Cursus

ChIP-seq with Bioconductor in R

GemiddeldVaardigheidsniveau
4 uur
102
Learn how to analyse and interpret ChIP-seq data with the help of Bioconductor using a human cancer dataset.

Cursus

Intermediate Network Analysis in Python

GevorderdVaardigheidsniveau
4 uur
102
Analyze time series graphs, use bipartite graphs, and gain the skills to tackle advanced problems in network analytics.

Cursus

Bayesiaans modelleren met RJAGS

GevorderdVaardigheidsniveau
4 uur
82
In deze cursus leer je hoe je met RJAGS meer geavanceerde Bayesiaanse modellen kunt maken.

Cursus

Casestudies: netwerkanalyse in R

BasisVaardigheidsniveau
4 uur
81
Pas de basisprincipes van netwerkanalyse toe op grote datasets uit de praktijk in 4 verschillende casestudys.

Cursus

Responsmodellen bouwen in R

GemiddeldVaardigheidsniveau
4 uur
60
Leer simpele modellen maken van hoe de markt reageert om je marketingplannen nog beter te maken.

Cursus

Vraag naar producten voorspellen in R

GemiddeldVaardigheidsniveau
4 uur
58
Learn how to identify important drivers of demand, look at seasonal effects, and predict demand for a hierarchy of products from a real world example.

Cursus

Mixture Models in R

GemiddeldVaardigheidsniveau
4 uur
53
Leer over mengmodellen: een handig en formeel statistisch kader voor probabilistische clustering en classificatie.

Cursus

Kanspuzzels in R

BasisVaardigheidsniveau
4 uur
50
Leer strategieën om kansberekeningen in R op te lossen door verschillende kansberekeningspuzzels te doen.

Cursus

Predictive Analytics met netwerkgdata in R

GemiddeldVaardigheidsniveau
4 uur
30
Leer labels van knooppunten in netwerken te voorspellen met behulp van netwerkleren en door beschrijvende kenmerken uit het netwerk te halen.

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Frequently asked questions

How does probability and statistics related to data science?

Probability and statistics are foundational to data science, offering the tools and frameworks necessary for analyzing data, making predictions, and deriving meaningful insights. They enable data scientists to understand patterns, assess uncertainties, and make informed decisions based on data analysis.

Why is it important to develop knowledge in probability and statistics?

Developing knowledge in probability and statistics is crucial for effectively interpreting data and making reliable predictions. This understanding forms the basis for designing experiments, analyzing results, and validating conclusions in various fields, ensuring decisions are data-driven and evidence-based.

What careers can I pursue with knowledge in probability and statistics?

With knowledge in probability and statistics, you can pursue a wide array of careers such as data scientist, market researcher, machine learning engineer, statistical analyst, and risk manager. These roles span various industries including finance, healthcare, technology, and government, where interpreting data and making evidence-based decisions are key.

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