generated from jhudsl/OTTR_Template
-
Notifications
You must be signed in to change notification settings - Fork 3
/
index.Rmd
22 lines (18 loc) · 1.82 KB
/
index.Rmd
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
---
title: "Statistical Inference"
date: "`r format(Sys.time(), '%B, %Y')`"
site: bookdown::bookdown_site
documentclass: book
bibliography: [book.bib]
biblio-style: apalike
link-citations: yes
description: "Description about Course/Book."
favicon: assets/dasl_favicon.ico
output:
bookdown::word_document2:
toc: true
---
# About this Course {-}
We are delighted that you've chosen to enroll in Statistical Inference, a part of the Data Science Specialization offered by Johns Hopkins Biostatistics! This course will introduce you to the essential concepts of statistical inference, which will serve as a solid foundation for the rest of your journey in the Data Science track. We strongly believe that the core essence of Data Science lies in its scientific approach.
The primary focus of this Specialization is to provide you with three key elements: Firstly, it will introduce you to the fundamental principles of working with data in a scientific manner, enabling you to derive new and reproducible insights. Secondly, it will equip you with the necessary tools to execute a data analytic strategy, starting from raw data stored in a database and culminating in a comprehensive report with interactive visualizations. Lastly, we emphasize hands-on practice, allowing you to gain practical experience and develop your skills through firsthand application of the techniques taught. This course serves as the fundamental and foundational component of the entire series. While minimizing the reliance on complex mathematics, we aim to provide students with the essential knowledge of utilizing statistics to draw inferences about populations.
We are thrilled about the prospect of expanding Data Science education at scale. Our intention is to create self-contained, fast-paced, and interactive courses that foster an engaging learning experience.