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Learn By Example: Statistics and Data Science in R [Video]
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-
Free ChapterIntroduction
-
The 10 second answer: Descriptive Statistics
-
Inferential Statistics
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Case studies in Inferential Statistics
- Case Study 1: Football Players (Estimating Population Mean from a Sample)
- Case Study 2: Election Polling (Estimating Population Proportion from a Sample)
- Case Study 3: A Medical Study (Hypothesis Test for the Population Mean)
- Case Study 4: Employee Behaviour (Hypothesis Test for the Population Proportion)
- Case Study 5: A/B Testing (Comparing the means of two populations)
- Case Study 6: Customer Analysis (Comparing the proportions of 2 populations)
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Diving into R
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Vectors
- Data Structures are the building blocks of R
- Creating a Vector
- The Mode of a Vector
- Vectors are Atomic
- Doing something with each element of a Vector
- Aggregating Vectors
- Operations between vectors of the same length
- Operations between vectors of different length
- Generating Sequences
- Using conditions with Vectors
- Find the lengths of multiple strings using Vectors
- Generate a complex sequence (using recycling)
- Vector Indexing (using numbers)
- Vector Indexing (using conditions)
- Vector Indexing (using names)
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Arrays
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Matrices
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Factors
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Lists and Data Frames
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Regression quantifies relationships between variables
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Linear Regression in Excel
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Linear Regression in R
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Data Visualization in R
About this
video
This course is a gentle yet thorough introduction to Data Science, Statistics and R using real life examples. Let’s parse that. Gentle, yet thorough: This course does not require a prior quantitative or mathematics background. It starts by introducing basic concepts such as the mean, median etc. and eventually covers all aspects of an analytics (or) data science career from analyzing and preparing raw data to visualizing your findings. Data Science, Statistics and R: This course is an introduction to Data Science and Statistics using the R programming language. It covers both the theoretical aspects of Statistical concepts and the practical implementation using R. Real life examples: Every concept is explained with the help of examples, case studies and source code in R wherever necessary. The examples cover a wide array of topics and range from A/B testing in an Internet company context to the Capital Asset Pricing Model in a quant finance context.
Style and Approach
With no prerequisites to the course, this is the hands-on course for Statistics and Data Science.
- Publication date:
- December 2017
- Publisher
- Packt
- Duration
- 9 hours 7 minutes
- ISBN
- 9781788996877
Download code from GitHub
Latest Reviews
(2 reviews total)
Very good presentation , but some time I get bad quality audio
4
Download link does not work
1