Statistics and Data Science Course

4.2

(22 reviews)

8 Lessons
204 Students
Certificate of completion

Track:

Computer Science

How is statistics used in data science? Building models using popular statistical methods such as Regression, Classification, Time Series Analysis and Hypothesis Testing. Data Scientists run suitable experiments and interpret the results with the help of these statistical methods. Statistics is also used for summarizing the data fairly quickly.Is statistics and data science the same? Statistics is a mathematically-based field which seeks to collect and interpret quantitative data. In contrast, data science is a multidisciplinary field which uses scientific methods, processes, and systems to extract knowledge from data in a range of forms.Is statistics good for data science? In our view, statistical methods are crucial in most fundamental steps of Data Science. ... Statistics is one of the most important disciplines to provide tools and methods to find structure in and to give deeper insight into data, and the most important discipline to analyze and quantify uncertainty.Is a statistician a data scientist? While data scientists focus on comparing a number of different methods to create the best machine learning model, statisticians rather work to improve a single, simple model to best fit the data. Statisticians tend to focus more on quantifying uncertainty than data scientists.Can you learn statistics on your own? Most people don't really learn statistics until they start analyzing data in their own research. Yes, it makes those classes tough. You need to acquire the knowledge before you can truly understand it. ... The only way to learn how to analyze data is to analyze some.

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What You'll Learn

Apply statistical methods such as regression, classification, and hypothesis testing to analyze data effectively
Build predictive models using time series analysis and statistical techniques for real-world data science applications
Interpret experimental results and quantify uncertainty using statistical tools in data science projects
Summarize complex datasets quickly and accurately with descriptive statistics and data visualization techniques
Differentiate between statistics and data science, understanding their roles in data analysis and decision-making
Utilize scientific methods and statistical tools to extract insights and structure from diverse data sources