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Statistics for Data Analysis Using Python
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[TutsNode.com] - Statistics for Data Analysis Using Python (Size: 6.75 GB) (Files: 390)
[TutsNode.com] - Statistics for Data Analysis Using Python
4. Pandas Package
10. DataFrame - Dealing with Rows.mp4
1.1 Piece_Dim.csv
12. Solution What is the Temperature on Monday.html
1.2 Section 4.ipynb
2.1 Section 4.ipynb
10. DataFrame - Dealing with Rows.srt
6. Reading a .csv File (Importing External Data).srt
2. Pandas Series.srt
9. DataFrame - Dealing with Columns.srt
1. Download Section 4 Resources.html
4. Create a DataFrame.html
5. Solution Create a DataFrame.html
6.1 Piece_Dim.csv
7. Importing a CSV file.html
8. Solution Importing a CSV file.html
3. Pandas DataFrame.srt
11. What is the Temperature on Monday.html
2. Pandas Series.mp4
6. Reading a .csv File (Importing External Data).mp4
9. DataFrame - Dealing with Columns.mp4
3. Pandas DataFrame.mp4
3. NumPy Package, Probability Distributions and an Introduction to SciPy Package
1.1 Section 3.ipynb
27. Introducing SciPy Package for Binomial Distributions.srt
4. Solution Two Dimensional Array.html
2.1 Section 3.ipynb
2. NumPy - Part 1.srt
19. Generating Random Numbers to Simulate the Probability.srt
24. [Theory] Binomial Distribution.srt
1. Download Section 3 Resources.html
26. Binomial Distribution Using NumPy.srt
3. Two Dimensional Array.html
5. Creating a Numpy array.html
6. Solution Creating a Numpy array.html
8. Filtering from an Array.html
9. Solution Filtering from an Array.html
10. Select a subsection of an Array.html
11. Solution Select a subsection of an Array.html
29. Solution Flipping a Coin.html
24. [Theory] Binomial Distribution.mp4
13. Divide the Array elements by 10.html
14. Solution Divide the array elements by 10.html
7. NumPy - Part 2.srt
46. Normal Distribution Using SciPy.srt
37. Poisson Distribution Using SciPy.srt
18. Quiz Basics of Probability.html
21. Generate Five Random Numbers.html
22. Solution Generate Five Random Numbers.html
16. [Theory] Basics of Probability - Part 2.srt
25. Quiz Binomial Distribution.html
42. [Theory] Normal Distribution - Part 1.srt
28. Flipping a Coin.html
45. Normal Distribution Using NumPy.srt
30. Let's Flip Again.html
31. Solution Let's Flip Again.html
32. Number of defectives in a selection.html
33. Solution Number of defectives in a selection.html
43. [Theory] Normal Distribution - Part 2.srt
49. Descriptive Statistics Using NumPy.srt
12. NumPy - Part 3.srt
38. Receiving Phone Calls.html
39. Solution Receiving Phone Calls.html
40. Probability of more than 6 calls.html
41. Solution Probability of more than 6 calls.html
44. Quiz Normal Distrubution.html
17. [Theory] Basics of Probability - Part 3.srt
47. Area of curve between two values of z.html
48. Solution Area of curve between two values of z.html
20. A Sample Probability Question.srt
50. Mean of Rows.html
51. Solution Mean of Rows.html
15. [Theory] Basics of Probability - Part 1.srt
36. Poisson Distribution Using NumPy.srt
23. [Theory] Probability Distributions - Introduction.srt
34. [Theory] Poisson Distribution.srt
35. [Theory] Poisson Distributions - An Example.srt
27. Introducing SciPy Package for Binomial Distributions.mp4
46. Normal Distribution Using SciPy.mp4
42. [Theory] Normal Distribution - Part 1.mp4
16. [Theory] Basics of Probability - Part 2.mp4
19. Generating Random Numbers to Simulate the Probability.mp4
43. [Theory] Normal Distribution - Part 2.mp4
37. Poisson Distribution Using SciPy.mp4
7. NumPy - Part 2.mp4
2. NumPy - Part 1.mp4
45. Normal Distribution Using NumPy.mp4
26. Binomial Distribution Using NumPy.mp4
12. NumPy - Part 3.mp4
34. [Theory] Poisson Distribution.mp4
17. [Theory] Basics of Probability - Part 3.mp4
49. Descriptive Statistics Using NumPy.mp4
35. [Theory] Poisson Distributions - An Example.mp4
20. A Sample Probability Question.mp4
15. [Theory] Basics of Probability - Part 1.mp4
36. Poisson Distribution Using NumPy.mp4
23. [Theory] Probability Distributions - Introduction.mp4
5. Data Visualization Using Matplotlib.pyplot and Seaborn Libraries
10. Visualizing the Titanic dataset.srt
1.1 Section 5.ipynb
7. Seaborn - Displot group of plots.srt
2. Histogram using matplotlib.pyplot.srt
8. Seaborn - Catplot group of plots.srt
3. Box Plot using matplotlib.pyplot.srt
9. Seaborn - Relplot group of plots.srt
4. Line and Scatter Plots using matplotlib.pyplot.srt
5. Bar Plot using matplotlib.pyplot.srt
1. Download Section 5 Resources.html
1.2 Piece_Dim.csv
6. Saving the plot as .png or .jpg.srt
10. Visualizing the Titanic dataset.mp4
9. Seaborn - Relplot group of plots.mp4
7. Seaborn - Displot group of plots.mp4
3. Box Plot using matplotlib.pyplot.mp4
8. Seaborn - Catplot group of plots.mp4
2. Histogram using matplotlib.pyplot.mp4
4. Line and Scatter Plots using matplotlib.pyplot.mp4
5. Bar Plot using matplotlib.pyplot.mp4
6. Saving the plot as .png or .jpg.mp4
1. Introduction
3. Download Section 1 Resources and the Course Slides.html
6. Introduction to coding exercises.html
7. Solution Introduction to coding exercises.html
9. Select an element from the list.html
10. Solution Select an element from the list.html
12. A review of lists.html
13. Solution A review of lists.html
3.1 Section 1.ipynb
8. Working with a List - Part 1.srt
4. Getting started with Python.srt
2. Getting started with Jupyter Notebook.srt
1. Installing Anaconda.srt
14. Working with a Dictionary.srt
11. Working with a List - Part 2.srt
5. Variables and Data Types.srt
17. Logical Operators.srt
15. Working with a Tuple.srt
16. Working with a Set.srt
8. Working with a List - Part 1.mp4
4. Getting started with Python.mp4
1. Installing Anaconda.mp4
2. Getting started with Jupyter Notebook.mp4
14. Working with a Dictionary.mp4
5. Variables and Data Types.mp4
11. Working with a List - Part 2.mp4
17. Logical Operators.mp4
15. Working with a Tuple.mp4
16. Working with a Set.mp4
3.2 Python Statistics Slides.pdf
8. Hypothesis Testing Part 2 (Two Sample Tests, ANOVA, GoF & Contingency Tables)
1.2 Section 8.ipynb
2.1 Section 8.ipynb
30. Contingency Tables Using Python.srt
23. [Theory] Performing ANOVA by Manual Calculations.srt
17. [Theory] Two Variances Test.srt
25. Conducting ANOVA Using Python - mpg Dataset.srt
18. Two Variances Test Using Python.srt
4. Two Sample z Test Using Python.srt
26. [Theory] Goodness of Fit.srt
8. [Theory] Two Sample t Test - Unequal Variance.srt
28. [Theory] Contingency Tables.srt
11. [Theory] Paired t Test.srt
6. [Theory] Two Sample t Test - Conditions and Calculations.srt
27. Goodness of Fit Test Using Python.srt
7. [Theory] Two Sample t Test - Equal Variance.srt
15. [Theory] Two Proportions Test - An Example of Pooled Method.srt
5. Two Sample z Test Using Python - tips Dataset.srt
21. [Theory] ANOVA - Conceptual Understanding.srt
16. Two Proportions Test Using Python.srt
22. [Theory] Statistics behind ANOVA.srt
24. Conducting ANOVA Using Python.srt
10. Two Sample t Test Using Python.srt
19. [Theory] ANOVA - Introduction.srt
13. [Theory] Two Proportions Test - Introduction.srt
3. [Theory] Two Sample z Test - Example.srt
20. [Theory] Why ANOVA.srt
2. [Theory] Two Sample z Test - Introduction.srt
9. [Theory] Two Sample t Test - Visual Interpretation.srt
12. Paired t Test Using Python.srt
14. [Theory] Two Proportions Test - Pooled vs Unpooled Method.srt
1.1 Two Machines.csv
29. Quiz Hypothesis Testing Part 2.html
1. Download Section 8 Resources.html
8. [Theory] Two Sample t Test - Unequal Variance.mp4
30. Contingency Tables Using Python.mp4
17. [Theory] Two Variances Test.mp4
11. [Theory] Paired t Test.mp4
7. [Theory] Two Sample t Test - Equal Variance.mp4
25. Conducting ANOVA Using Python - mpg Dataset.mp4
23. [Theory] Performing ANOVA by Manual Calculations.mp4
26. [Theory] Goodness of Fit.mp4
18. Two Variances Test Using Python.mp4
27. Goodness of Fit Test Using Python.mp4
4. Two Sample z Test Using Python.mp4
15. [Theory] Two Proportions Test - An Example of Pooled Method.mp4
6. [Theory] Two Sample t Test - Conditions and Calculations.mp4
28. [Theory] Contingency Tables.mp4
5. Two Sample z Test Using Python - tips Dataset.mp4
24. Conducting ANOVA Using Python.mp4
16. Two Proportions Test Using Python.mp4
13. [Theory] Two Proportions Test - Introduction.mp4
10. Two Sample t Test Using Python.mp4
20. [Theory] Why ANOVA.mp4
14. [Theory] Two Proportions Test - Pooled vs Unpooled Method.mp4
3. [Theory] Two Sample z Test - Example.mp4
19. [Theory] ANOVA - Introduction.mp4
21. [Theory] ANOVA - Conceptual Understanding.mp4
9. [Theory] Two Sample t Test - Visual Interpretation.mp4
22. [Theory] Statistics behind ANOVA.mp4
12. Paired t Test Using Python.mp4
2. [Theory] Two Sample z Test - Introduction.mp4
6. Inferential Statistics and Hypothesis Testing - Introduction
5. Central Limit Theorem - Using Python.srt
5. Central Limit Theorem - Using Python.mp4
2. [Theory] Population vs Samples.srt
1.1 Section 6.ipynb
2.1 Section 6.ipynb
9. [Theory] Hypothesis Testing - A Simple Introduction.srt
11. [Theory] Types of Errors - Summary.srt
12. [Theory] Hypothesis Testing - An Overview.srt
10. [Theory] Types of Errors - Type I and Type II Errors.srt
16. Hypothesis Testing Using Python.srt
3. [Theory] Central Limit Theorem.srt
13. [Theory] Z Tables - Finding the Critical Values.srt
7. [Theory] Statistical and Practical Significance.srt
1. Download Section 6 Resources.html
4. Quiz Population vs Samples + Central Limit Theorem.html
15. Quiz Hypothesis Testing Basics.html
14. [Theory] The p-Value.srt
8. [Theory] Null and Alternate Hypothesis.srt
6. [Theory] Basics of Hypothesis Testing.srt
16. Hypothesis Testing Using Python.mp4
13. [Theory] Z Tables - Finding the Critical Values.mp4
9. [Theory] Hypothesis Testing - A Simple Introduction.mp4
11. [Theory] Types of Errors - Summary.mp4
12. [Theory] Hypothesis Testing - An Overview.mp4
10. [Theory] Types of Errors - Type I and Type II Errors.mp4
3. [Theory] Central Limit Theorem.mp4
2. [Theory] Population vs Samples.mp4
14. [Theory] The p-Value.mp4
7. [Theory] Statistical and Practical Significance.mp4
8. [Theory] Null and Alternate Hypothesis.mp4
6. [Theory] Basics of Hypothesis Testing.mp4
7. Hypothesis Testing Part 1 (One Sample Tests)
5. One Sample Z Test - Examples.srt
1.3 Section 7.ipynb
2.1 Section 7.ipynb
6. One Sample Z Test Using Python.srt
9. [Theory] One Proportion Test.srt
10. One Proportion Test Using Python.srt
14. One Variance Test Using Python.srt
7. One Sample t Test.srt
2. [Theory] Tests for means, variances and proportions - Introduction.srt
3. [Theory] One Sample Z Test - Conditions.srt
12. [Theory] One Variance Test - Example 1.srt
4. [Theory] One Sample Z Test.srt
13. [Theory] One Variance Test - Example 2.srt
8. One Sample t Test Using Python.srt
1. Download Section 7 Resources.html
11. [Theory] One Variance Test - Introduction.srt
1.2 Smokers.csv
10.1 Smokers.csv
1.1 Machine1.csv
6.1 Machine1.csv
15. Quiz Hypothesis Testing Part 1.html
2. [Theory] Tests for means, variances and proportions - Introduction.mp4
9. [Theory] One Proportion Test.mp4
6. One Sample Z Test Using Python.mp4
4. [Theory] One Sample Z Test.mp4
7. One Sample t Test.mp4
10. One Proportion Test Using Python.mp4
14. One Variance Test Using Python.mp4
13. [Theory] One Variance Test - Example 2.mp4
12. [Theory] One Variance Test - Example 1.mp4
3. [Theory] One Sample Z Test - Conditions.mp4
5. One Sample Z Test - Examples.mp4
8. One Sample t Test Using Python.mp4
11. [Theory] One Variance Test - Introduction.mp4
2. Descriptive Statistics
1. Download Section 2 Resources.html
5. Quiz Descriptive Statistics.html
7. Find the mean, mode, median and standard deviation.html
8. Solution Find the mean, mode, median and standard deviation.html
9. Find the Inter Quartile Range.html
10. Solution Find the Inter Quartile Range.html
6. Descriptive Statistics Using Python.srt
1.1 Section 2.ipynb
2. [Theory] Measurement of Central Tendency.srt
3. [Theory] Measurement of Dispersion - Part 1.srt
4. [Theory] Measurement of Dispersion - Part 2.srt
6. Descriptive Statistics Using Python.mp4
2. [Theory] Measurement of Central Tendency.mp4
3. [Theory] Measurement of Dispersion - Part 1.mp4
4. [Theory] Measurement of Dispersion - Part 2.mp4
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