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.
|The Need for Statistics||00:04:00|
|Introduction to RStudio||00:06:00|
|Functions and Objects||00:05:00|
|Importing a Data Frame||00:06:00|
|Indexing Data Frames||00:10:00|
|Graphs to Tell the Story of Our Data||00:04:00|
|Graphing a Single Variable||00:05:00|
|Center and Spread||00:02:00|
|Visualizing Univariate Data||00:08:00|
|Histograms by Groups||00:08:00|
|Univariate Descriptive Statistics||00:03:00|
|The Origin of “r”||00:04:00|
|Scatterplots and the “r” Value||00:06:00|
|Linearity and the Correlation Coefficient||00:05:00|
|Submit Your Assignment||00:00:00|
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