enthaltenWelcome to the Ball State University course 鈥淪tatistical Methods for Data Science.鈥� As the title suggests, this course provides fundamental concepts and methods for data-generating mechanisms such as probability models and inferential methods such as estimation and hypothesis testing. scientists. You will need the right tools and analytics methods to make good sense of data and to make data-driven decisions. We are going to take a systematic approach to build a strong foundation on probability and probability models, large sample theory as a bridge between probability theory and inference, and basic inferential processes. Please note that as data scientists, it is important for us to be able to connect data and learn how the world around us works. To accomplish this challenging task, we will learn how we can connect data through probability theory and statistical models and take actionable decisions, confirm a hypothesis, or make predictions.
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Kompetenzen, die Sie erwerben
- Kategorie: Statistical Inference
- Kategorie: Sampling (Statistics)
- Kategorie: Statistical Modeling
- Kategorie: Statistical Visualization
- Kategorie: R Programming
- Kategorie: Probability
- Kategorie: Statistical Methods
- Kategorie: Probability Distribution
- Kategorie: Data Science
- Kategorie: Statistical Analysis
- Kategorie: Bayesian Statistics
- Kategorie: Probability & Statistics
Wichtige Details
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In diesem Kurs gibt es 5 Module
Welcome!听In part 1 of this module you will complete a recommended听reading听about the听course and听post听on a discussion board entry to introduce yourself to your classmates.听In听part听2听of听this module,听we will review probability theory and its applications听to real-world problem-solving.听听Probability听is a measure of听the chance听of听occurrence of a future event.听For example, what is the probability that you听will听see two heads when you toss two coins?听It is 录, right? Why do听you care about learning probability?听Here is a quote by the ancient Greek philosopher Democritus听鈥淓verything existing in the universe is the fruit of chance鈥�.听Thus, it is important for us to have basic probability knowledge. In听data听science,听听probability听helps听us听understand how听data听is听generated听and plays听a major role听in inference and prediction.In this module, we will review three definitions of probability, probability laws, conditional probability, and Bayes' rule.听Knowledge of conditional probability is essential in most practical problems. Bayes' rule provides a mechanism for determining conditional probabilities when prior probabilities are given.听
Das ist alles enthalten
12 Videos7 Lekt眉ren1 Aufgabe1 peer review1 Unbewertetes Labor
In this module, we will talk about random variables which are basically a mapping or correspondence between the sample space of a random experiment and the real number system.
Das ist alles enthalten
10 Videos6 Lekt眉ren2 Aufgaben1 Unbewertetes Labor
In this module, we will learn about discrete probability distributions based on what is known as Bernoulli Trials. You will learn about Bernoulli, Binomial, Geometric, and Negative Binomial Distributions. These distributions are widely used in numerous applications including health and biomedical sciences, social sciences, environmental sciences, finance and business, and education among others.
Das ist alles enthalten
10 Videos6 Lekt眉ren2 Aufgaben
This module covers continuous probability distributions. In the real world, not all random variables are discrete. For example, daily rainfall amount, the lifetime of an equipment, biological measures such as the body mass index or BMI and Cholesterol levels, and various test scores take values in intervals and are called continuous random variables.
Das ist alles enthalten
11 Videos8 Lekt眉ren1 Aufgabe1 Programmieraufgabe1 peer review1 Unbewertetes Labor
In this module, we will revisit Normal distribution and its attractive properties. You will see how the law of large numbers can be used to approximate the distributions of sum or average of sample data.
Das ist alles enthalten
14 Videos5 Lekt眉ren1 Aufgabe1 Programmieraufgabe1 peer review2 Unbewertete Labore
Auf einen Abschluss hinarbeiten
Dieses Kurs ist Teil des/der folgenden Studiengangs/Studieng盲nge, die von Ball State Universityangeboten werden. Wenn Sie zugelassen werden und sich immatrikulieren, k枚nnen Ihre abgeschlossenen Kurse auf Ihren Studienabschluss angerechnet werden und Ihre Fortschritte k枚nnen mit Ihnen 眉bertragen werden.鹿
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H盲ufig gestellte Fragen
To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
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You will be eligible for a full refund until two weeks after your payment date, or (for courses that have just launched) until two weeks after the first session of the course begins, whichever is later. You cannot receive a refund once you鈥檝e earned a Course Certificate, even if you complete the course within the two-week refund period. See our full refund policy.
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