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E-raamat: Advancing into Analytics

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  • Formaat: 250 pages
  • Ilmumisaeg: 22-Jan-2021
  • Kirjastus: O'Reilly Media
  • Keel: eng
  • ISBN-13: 9781492094296
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Advancing into AnalyticsSuurem pilt
  • Formaat: 250 pages
  • Ilmumisaeg: 22-Jan-2021
  • Kirjastus: O'Reilly Media
  • Keel: eng
  • ISBN-13: 9781492094296
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Data analytics may seem daunting, but if you're an experienced Excel user, you have a unique head start. With this hands-on guide, intermediate Excel users will gain a solid understanding of analytics and the data stack. By the time you complete this book, you'll be able to conduct exploratory data analysis and hypothesis testing using a programming language.

Exploring and testing relationships are core to analytics. By using the tools and frameworks in this book, you'll be well positioned to continue learning more advanced data analysis techniques. Author George Mount, founder and CEO of Stringfest Analytics, demonstrates key statistical concepts with spreadsheets, then pivots your existing knowledge about data manipulation into R and Python programming.

This practical book guides you through:

  • Foundations of analytics in Excel: Use Excel to test relationships between variables and build compelling demonstrations of important concepts in statistics and analytics
  • From Excel to R: Cleanly transfer what you've learned about working with data from Excel to R
  • From Excel to Python: Learn how to pivot your Excel data chops into Python and conduct a complete data analysis
Preface ix
Part I Foundations of Analytics in Excel
1 Foundations of Exploratory Data Analysis
3(24)
What Is Exploratory Data Analysis?
3(2)
Observations
5(1)
Variables
5(4)
Demonstration: Classifying Variables
9(2)
Recap: Variable Types
11(1)
Exploring Variables in Excel
11(1)
Exploring Categorical Variables
12(3)
Exploring Quantitative Variables
15(11)
Conclusion
26(1)
Exercises
26(1)
2 Foundations of Probability
27(14)
Probability and Randomness
27(1)
Probability and Sample Space
28(1)
Probability and Experiments
28(1)
Unconditional and Conditional Probability
28(1)
Probability Distributions
29(1)
Discrete Probability Distributions
29(3)
Continuous Probability Distributions
32(8)
Conclusion
40(1)
Exercises
40(1)
3 Foundations of Inferential Statistics
41(20)
The Framework of Statistical Inference
42(1)
Collect a Representative Sample
42(1)
State the Hypotheses
43(2)
Formulate an Analysis Plan
45(2)
Analyze the Data
47(3)
Make a Decision
50(7)
It's Your World the Data's Only Living in It
57(1)
Conclusion
58(1)
Exercises
59(2)
4 Correlation and Regression
61(18)
"Correlation Does Not Imply Causation"
61(1)
Introducing Correlation
62(5)
From Correlation to Regression
67(2)
Linear Regression in Excel
69(6)
Rethinking Our Results: Spurious Relationships
75(1)
Conclusion
76(1)
Advancing into Programming
77(1)
Exercises
77(2)
5 The Data Analytics Stack
79(14)
Statistics Versus Data Analytics Versus Data Science
79(1)
Statistics
79(1)
Data Analytics
80(1)
Business Analytics
80(1)
Data Science
80(1)
Machine Learning
81(1)
Distinct, but Not Exclusive
81(1)
The Importance of the Data Analytics Stack
81(1)
Spreadsheets
82(3)
Databases
85(1)
Business Intelligence Platforms
86(1)
Data Programming Languages
87(1)
Conclusion
88(1)
What's Next
89(1)
Exercises
89(4)
Part II From Excel to R
6 First Steps with R for Excel Users
93(16)
Downloading R
93(1)
Getting Started with RStudio
94(9)
Packages in R
103(1)
Upgrading R, RStudio, and R Packages
104(1)
Conclusion
105(2)
Exercises
107(2)
7 Data Structures in R
109(14)
Vectors
109(2)
Indexing and Subsetting Vectors
111(1)
From Excel Tables to R Data Frames
112(3)
Importing Data in R
115(3)
Exploring a Data Frame
118(2)
Indexing and Subsetting Data Frames
120(1)
Writing Data Frames
121(1)
Conclusion
122(1)
Exercises
122(1)
8 Data Manipulation and Visualization in R
123(22)
Data Manipulation with dplyr
124(1)
Column-Wise Operations
124(3)
Row-Wise Operations
127(2)
Aggregating and Joining Data
129(3)
dplyr and the Power of the Pipe (% < %)
132(2)
Reshaping Data with tidyr
134(2)
Data Visualization with ggplot2
136(6)
Conclusion
142(1)
Exercises
143(2)
9 Capstone: R for Data Analytics
145(16)
Exploratory Data Analysis
146(4)
Hypothesis Testing
150(1)
Independent Samples t-test
151(2)
Linear Regression
153(2)
Train/Test Split and Validation
155(3)
Conclusion
158(1)
Exercises
158(3)
Part III From Excel to Python
10 First Steps with Python for Excel Users
161(14)
Downloading Python
161(1)
Getting Started with Jupyter
162(8)
Modules in Python
170(2)
Upgrading Python, Anaconda, and Python packages
172(1)
Conclusion
172(1)
Exercises
173(2)
11 Data Structures in Python
175(12)
NumPy arrays
176(2)
Indexing and Subsetting NumPy Arrays
178(1)
Introducing Pandas DataF rames
179(1)
Importing Data in Python
180(2)
Exploring a DataFrame
182(1)
Indexing and Subsetting DataFrames
183(1)
Writing DataFrames
184(1)
Conclusion
184(1)
Exercises
185(2)
12 Data Manipulation and Visualization in Python
187(16)
Column-Wise Operations
188(2)
Row-Wise Operations
190(2)
Aggregating and Joining Data
192(1)
Reshaping Data
193(2)
Data Visualization
195(5)
Conclusion
200(1)
Exercises
201(2)
13 Capstone: Python for Data Analytics
203(10)
Exploratory Data Analysis
204(2)
Hypothesis Testing
206(1)
Independent Samples T-test
207(1)
Linear Regression
208(1)
Train/Test Split and Validation
209(2)
Conclusion
211(1)
Exercises
211(2)
14 Conclusion and Next Steps
213(4)
Further Slices of the Stack
213(1)
Research Design and Business Experiments
213(1)
Further Statistical Methods
214(1)
Data Science and Machine Learning
214(1)
Version Control
214(1)
Ethics
215(1)
Go Forth and Data How You Please
215(1)
Parting Words
216(1)
Index 217
George Mount is the founder and CEO of Stringfest Analytics, a consulting firm specializing in analytics education and upskilling. He has worked with leading bootcamps, learning platforms and practice organizations to help individuals excel at analytics. George regularly blogs and speaks on data analysis, data education and workforce development.

George holds a bachelor's degree in economics from Hillsdale College and master's degrees in finance and information systems from Case Western Reserve University.
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