Data Scientist 14: Data Research Statistical Approaches
Overview/Description
Expected Duration
Lesson Objectives
Course Number
Expertise Level
Overview/Description
Discover how to apply statistical algorithms like PDF, CDF, binomial distribution, and interval estimation for data research. How to implement visualizations to graphically represent the outcomes of data research is also covered.

Expected Duration (hours)
0.7

Lesson Objectives Data Scientist 14: Data Research Statistical Approaches

describe the features provided by statistical methods and approaches in data research
identify the relevance of discrete vs continuous distribution in simplifying data research
recognize the features of PDF and CDF from the perspective of data research
implement binomial distribution using R
specify the types of interval estimation that can be used to enhance data research
implement point and interval estimation using R
describe the relevance of data visualization techniques in projecting the outcome of data research
plot visualizations using R to depict the outcome of data research graphically
recall the data integration techniques that facilitate using statistical methods
create Histograms, Scatter plots, and Box plots using Python libraries
implement missing values and outliers using Python
implement data research using various statistical approaches

Course Number: it_dsdrptdj_03_enus

Expertise Level
Intermediate