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The goal of data analysis is to find actionable insights that can inform decision making. Data analysis can involve data mining, descriptive and predictive analysis, statistical analysis, business analytics and big data analytics. The [course_title] provides many of the common data analysis tools used to gather, analyze and adapt your data to feed business decisions. You do not need heavy Excel or data analysis experience. This course includes introductory exercises on Excel add-ins, standard deviation, random sampling, and an introduction to pivot tables and charts.


This course does not involve any written exams. Students need to answer 5 assignment questions to complete the course, the answers will be in the form of written work in pdf or word. Students can write the answers in their own time. Each answer needs to be 200 words (1 Page). Once the answers are submitted, the tutor will check and assess the work.


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Course Credit:  The University of Texas at Austin.

Course Curriculum

Lesson 1
The Need for Statistics 00:04:00
Variables 00:05:00
Introduction to RStudio 00:06:00
Functions and Objects 00:05:00
Vectors 00:05:00
Indexing +565 00:05:00
Importing a Data Frame 00:06:00
Indexing Data Frames 00:10:00
Lesson 2
Graphs to Tell the Story of Our Data 00:04:00
Graphing a Single Variable 00:05:00
Center and Spread 00:02:00
Using Z-Scores 00:07:00
Visualizing Univariate Data 00:08:00
Histograms by Groups 00:08:00
Univariate Descriptive Statistics 00:03:00
Lesson 3
The Origin of “r” 00:04:00
Scatterplots and the “r” Value 00:06:00
Linearity and the Correlation Coefficient 00:05:00
Scatterplots 00:08:00
Correlation 00:05:00
Submit Your Assignment 00:00:00
Certification 00:00:00

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