Statistics for Data Analysis Using Python | 449138D31AFE5ADC05FDAC98DDD42B4B34333D94

Statistics for Data Analysis Using Python

Name	Statistics for Data Analysis Using Python	DOWNLOAD Copy Link Trouble downloading? see How To
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Total Files	390
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Hash	449138D31AFE5ADC05FDAC98DDD42B4B34333D94

/4. Pandas Package/
10. DataFrame - Dealing with Rows.mp4	162.3 MB

TutsNode.com.txt	0.1 KB
[TGx]Downloaded from torrentgalaxy.to .txt	0.6 KB
/.../3. NumPy Package, Probability Distributions and an Introduction to SciPy Package/
1.1 Section 3.ipynb	203.6 KB
27. Introducing SciPy Package for Binomial Distributions.srt	23.0 KB
4. Solution Two Dimensional Array.html	0.1 KB
2.1 Section 3.ipynb	203.3 KB
2. NumPy - Part 1.srt	21.3 KB
19. Generating Random Numbers to Simulate the Probability.srt	19.4 KB
24. [Theory] Binomial Distribution.srt	19.2 KB
1. Download Section 3 Resources.html	0.1 KB
26. Binomial Distribution Using NumPy.srt	17.3 KB
3. Two Dimensional Array.html	0.1 KB
5. Creating a Numpy array.html	0.1 KB
6. Solution Creating a Numpy array.html	0.1 KB
8. Filtering from an Array.html	0.1 KB
9. Solution Filtering from an Array.html	0.1 KB
10. Select a subsection of an Array.html	0.1 KB
11. Solution Select a subsection of an Array.html	0.1 KB
29. Solution Flipping a Coin.html	0.1 KB
24. [Theory] Binomial Distribution.mp4	133.4 MB
13. Divide the Array elements by 10.html	0.1 KB
14. Solution Divide the array elements by 10.html	0.1 KB
7. NumPy - Part 2.srt	16.2 KB
46. Normal Distribution Using SciPy.srt	16.0 KB
37. Poisson Distribution Using SciPy.srt	15.9 KB
18. Quiz Basics of Probability.html	0.1 KB
21. Generate Five Random Numbers.html	0.1 KB
22. Solution Generate Five Random Numbers.html	0.1 KB
16. [Theory] Basics of Probability - Part 2.srt	15.3 KB
25. Quiz Binomial Distribution.html	0.1 KB
42. [Theory] Normal Distribution - Part 1.srt	14.6 KB
28. Flipping a Coin.html	0.1 KB
45. Normal Distribution Using NumPy.srt	14.5 KB
30. Let's Flip Again.html	0.1 KB
31. Solution Let's Flip Again.html	0.1 KB
32. Number of defectives in a selection.html	0.1 KB
33. Solution Number of defectives in a selection.html	0.1 KB
43. [Theory] Normal Distribution - Part 2.srt	14.2 KB
49. Descriptive Statistics Using NumPy.srt	13.7 KB
12. NumPy - Part 3.srt	13.2 KB
38. Receiving Phone Calls.html	0.1 KB
39. Solution Receiving Phone Calls.html	0.1 KB
40. Probability of more than 6 calls.html	0.1 KB
41. Solution Probability of more than 6 calls.html	0.1 KB
44. Quiz Normal Distrubution.html	0.1 KB
17. [Theory] Basics of Probability - Part 3.srt	11.9 KB
47. Area of curve between two values of z.html	0.1 KB
48. Solution Area of curve between two values of z.html	0.3 KB
20. A Sample Probability Question.srt	11.7 KB
50. Mean of Rows.html	0.1 KB
51. Solution Mean of Rows.html	0.6 KB
15. [Theory] Basics of Probability - Part 1.srt	10.5 KB
36. Poisson Distribution Using NumPy.srt	10.3 KB
23. [Theory] Probability Distributions - Introduction.srt	9.8 KB
34. [Theory] Poisson Distribution.srt	7.7 KB
35. [Theory] Poisson Distributions - An Example.srt	7.4 KB
27. Introducing SciPy Package for Binomial Distributions.mp4	113.3 MB
46. Normal Distribution Using SciPy.mp4	107.2 MB
42. [Theory] Normal Distribution - Part 1.mp4	94.7 MB
16. [Theory] Basics of Probability - Part 2.mp4	93.2 MB
19. Generating Random Numbers to Simulate the Probability.mp4	91.8 MB
43. [Theory] Normal Distribution - Part 2.mp4	87.0 MB
37. Poisson Distribution Using SciPy.mp4	80.2 MB
7. NumPy - Part 2.mp4	78.8 MB
2. NumPy - Part 1.mp4	78.6 MB
45. Normal Distribution Using NumPy.mp4	77.8 MB
26. Binomial Distribution Using NumPy.mp4	77.2 MB
12. NumPy - Part 3.mp4	76.7 MB
34. [Theory] Poisson Distribution.mp4	73.2 MB
17. [Theory] Basics of Probability - Part 3.mp4	72.8 MB
49. Descriptive Statistics Using NumPy.mp4	65.7 MB
35. [Theory] Poisson Distributions - An Example.mp4	63.4 MB
20. A Sample Probability Question.mp4	60.5 MB
15. [Theory] Basics of Probability - Part 1.mp4	54.0 MB
36. Poisson Distribution Using NumPy.mp4	48.7 MB
23. [Theory] Probability Distributions - Introduction.mp4	43.9 MB
/.../5. Data Visualization Using Matplotlib.pyplot and Seaborn Libraries/
10. Visualizing the Titanic dataset.srt	23.5 KB
1.1 Section 5.ipynb	891.3 KB
7. Seaborn - Displot group of plots.srt	19.3 KB
2. Histogram using matplotlib.pyplot.srt	13.2 KB
8. Seaborn - Catplot group of plots.srt	15.6 KB
3. Box Plot using matplotlib.pyplot.srt	14.0 KB
9. Seaborn - Relplot group of plots.srt	12.7 KB
4. Line and Scatter Plots using matplotlib.pyplot.srt	11.8 KB
5. Bar Plot using matplotlib.pyplot.srt	11.3 KB
1. Download Section 5 Resources.html	0.1 KB
1.2 Piece_Dim.csv	1.6 KB
6. Saving the plot as .png or .jpg.srt	5.6 KB
10. Visualizing the Titanic dataset.mp4	105.4 MB
9. Seaborn - Relplot group of plots.mp4	85.2 MB
7. Seaborn - Displot group of plots.mp4	80.5 MB
3. Box Plot using matplotlib.pyplot.mp4	78.2 MB
8. Seaborn - Catplot group of plots.mp4	71.2 MB
2. Histogram using matplotlib.pyplot.mp4	62.1 MB
4. Line and Scatter Plots using matplotlib.pyplot.mp4	56.7 MB
5. Bar Plot using matplotlib.pyplot.mp4	49.3 MB
6. Saving the plot as .png or .jpg.mp4	36.1 MB
/4. Pandas Package/
1.1 Piece_Dim.csv	1.6 KB
12. Solution What is the Temperature on Monday.html	0.4 KB
1.2 Section 4.ipynb	107.2 KB
2.1 Section 4.ipynb	107.2 KB
10. DataFrame - Dealing with Rows.srt	35.6 KB
6. Reading a .csv File (Importing External Data).srt	17.1 KB
2. Pandas Series.srt	14.7 KB
9. DataFrame - Dealing with Columns.srt	14.1 KB
1. Download Section 4 Resources.html	0.1 KB
4. Create a DataFrame.html	0.1 KB
5. Solution Create a DataFrame.html	0.4 KB
6.1 Piece_Dim.csv	1.6 KB
7. Importing a CSV file.html	0.1 KB
8. Solution Importing a CSV file.html	0.1 KB
3. Pandas DataFrame.srt	10.2 KB
11. What is the Temperature on Monday.html	0.1 KB
2. Pandas Series.mp4	91.2 MB
6. Reading a .csv File (Importing External Data).mp4	83.2 MB
9. DataFrame - Dealing with Columns.mp4	65.6 MB
3. Pandas DataFrame.mp4	55.5 MB
/1. Introduction/
3. Download Section 1 Resources and the Course Slides.html	0.2 KB
6. Introduction to coding exercises.html	0.1 KB
7. Solution Introduction to coding exercises.html	0.1 KB
9. Select an element from the list.html	0.1 KB
10. Solution Select an element from the list.html	0.1 KB
12. A review of lists.html	0.1 KB
13. Solution A review of lists.html	0.1 KB
3.1 Section 1.ipynb	36.9 KB
8. Working with a List - Part 1.srt	21.6 KB
4. Getting started with Python.srt	18.3 KB
2. Getting started with Jupyter Notebook.srt	12.1 KB
1. Installing Anaconda.srt	9.4 KB
14. Working with a Dictionary.srt	9.4 KB
11. Working with a List - Part 2.srt	8.4 KB
5. Variables and Data Types.srt	8.2 KB
17. Logical Operators.srt	5.3 KB
15. Working with a Tuple.srt	4.6 KB
16. Working with a Set.srt	4.0 KB
8. Working with a List - Part 1.mp4	87.5 MB
4. Getting started with Python.mp4	72.8 MB
1. Installing Anaconda.mp4	62.5 MB
2. Getting started with Jupyter Notebook.mp4	54.4 MB
14. Working with a Dictionary.mp4	45.0 MB
5. Variables and Data Types.mp4	40.2 MB
11. Working with a List - Part 2.mp4	36.5 MB
17. Logical Operators.mp4	29.5 MB
15. Working with a Tuple.mp4	26.8 MB
16. Working with a Set.mp4	16.7 MB
3.2 Python Statistics Slides.pdf	3.0 MB
/.../8. Hypothesis Testing Part 2 (Two Sample Tests, ANOVA, GoF & Contingency Tables)/
1.2 Section 8.ipynb	127.0 KB
2.1 Section 8.ipynb	127.0 KB
30. Contingency Tables Using Python.srt	18.9 KB
23. [Theory] Performing ANOVA by Manual Calculations.srt	18.3 KB
17. [Theory] Two Variances Test.srt	16.7 KB
25. Conducting ANOVA Using Python - mpg Dataset.srt	16.2 KB
18. Two Variances Test Using Python.srt	15.5 KB
4. Two Sample z Test Using Python.srt	15.5 KB
26. [Theory] Goodness of Fit.srt	15.4 KB
8. [Theory] Two Sample t Test - Unequal Variance.srt	15.0 KB
28. [Theory] Contingency Tables.srt	14.1 KB
11. [Theory] Paired t Test.srt	14.0 KB
6. [Theory] Two Sample t Test - Conditions and Calculations.srt	12.6 KB
27. Goodness of Fit Test Using Python.srt	12.1 KB
7. [Theory] Two Sample t Test - Equal Variance.srt	11.6 KB
15. [Theory] Two Proportions Test - An Example of Pooled Method.srt	10.9 KB
5. Two Sample z Test Using Python - tips Dataset.srt	10.8 KB
21. [Theory] ANOVA - Conceptual Understanding.srt	10.5 KB
16. Two Proportions Test Using Python.srt	9.6 KB
22. [Theory] Statistics behind ANOVA.srt	9.4 KB
24. Conducting ANOVA Using Python.srt	9.0 KB
10. Two Sample t Test Using Python.srt	7.9 KB
19. [Theory] ANOVA - Introduction.srt	7.8 KB
13. [Theory] Two Proportions Test - Introduction.srt	7.7 KB
3. [Theory] Two Sample z Test - Example.srt	7.5 KB
20. [Theory] Why ANOVA.srt	7.5 KB
2. [Theory] Two Sample z Test - Introduction.srt	7.3 KB
9. [Theory] Two Sample t Test - Visual Interpretation.srt	7.0 KB
12. Paired t Test Using Python.srt	6.1 KB
14. [Theory] Two Proportions Test - Pooled vs Unpooled Method.srt	5.3 KB
1.1 Two Machines.csv	3.6 KB
29. Quiz Hypothesis Testing Part 2.html	0.1 KB
1. Download Section 8 Resources.html	0.1 KB
8. [Theory] Two Sample t Test - Unequal Variance.mp4	109.3 MB
30. Contingency Tables Using Python.mp4	100.6 MB
17. [Theory] Two Variances Test.mp4	99.6 MB
11. [Theory] Paired t Test.mp4	93.3 MB
7. [Theory] Two Sample t Test - Equal Variance.mp4	92.6 MB
25. Conducting ANOVA Using Python - mpg Dataset.mp4	81.7 MB
23. [Theory] Performing ANOVA by Manual Calculations.mp4	78.7 MB
26. [Theory] Goodness of Fit.mp4	74.2 MB
18. Two Variances Test Using Python.mp4	72.4 MB
27. Goodness of Fit Test Using Python.mp4	70.7 MB
4. Two Sample z Test Using Python.mp4	70.1 MB
15. [Theory] Two Proportions Test - An Example of Pooled Method.mp4	62.6 MB
6. [Theory] Two Sample t Test - Conditions and Calculations.mp4	62.0 MB
28. [Theory] Contingency Tables.mp4	60.4 MB
5. Two Sample z Test Using Python - tips Dataset.mp4	58.5 MB
24. Conducting ANOVA Using Python.mp4	57.5 MB
16. Two Proportions Test Using Python.mp4	57.1 MB
13. [Theory] Two Proportions Test - Introduction.mp4	55.2 MB
10. Two Sample t Test Using Python.mp4	50.6 MB
20. [Theory] Why ANOVA.mp4	50.5 MB
14. [Theory] Two Proportions Test - Pooled vs Unpooled Method.mp4	48.9 MB
3. [Theory] Two Sample z Test - Example.mp4	42.4 MB
19. [Theory] ANOVA - Introduction.mp4	42.0 MB
21. [Theory] ANOVA - Conceptual Understanding.mp4	41.0 MB
9. [Theory] Two Sample t Test - Visual Interpretation.mp4	39.5 MB
22. [Theory] Statistics behind ANOVA.mp4	38.6 MB
12. Paired t Test Using Python.mp4	36.0 MB
2. [Theory] Two Sample z Test - Introduction.mp4	33.8 MB
/.../6. Inferential Statistics and Hypothesis Testing - Introduction/
5. Central Limit Theorem - Using Python.srt	23.4 KB
5. Central Limit Theorem - Using Python.mp4	134.1 MB
2. [Theory] Population vs Samples.srt	10.3 KB
1.1 Section 6.ipynb	73.0 KB
2.1 Section 6.ipynb	73.0 KB
9. [Theory] Hypothesis Testing - A Simple Introduction.srt	16.1 KB
11. [Theory] Types of Errors - Summary.srt	16.0 KB
12. [Theory] Hypothesis Testing - An Overview.srt	15.8 KB
10. [Theory] Types of Errors - Type I and Type II Errors.srt	15.6 KB
16. Hypothesis Testing Using Python.srt	15.2 KB
3. [Theory] Central Limit Theorem.srt	13.2 KB
13. [Theory] Z Tables - Finding the Critical Values.srt	11.2 KB
7. [Theory] Statistical and Practical Significance.srt	8.2 KB
1. Download Section 6 Resources.html	0.1 KB
4. Quiz Population vs Samples + Central Limit Theorem.html	0.1 KB
15. Quiz Hypothesis Testing Basics.html	0.1 KB
14. [Theory] The p-Value.srt	5.5 KB
8. [Theory] Null and Alternate Hypothesis.srt	4.4 KB
6. [Theory] Basics of Hypothesis Testing.srt	4.2 KB
16. Hypothesis Testing Using Python.mp4	107.5 MB
13. [Theory] Z Tables - Finding the Critical Values.mp4	104.9 MB
9. [Theory] Hypothesis Testing - A Simple Introduction.mp4	101.1 MB
11. [Theory] Types of Errors - Summary.mp4	94.0 MB
12. [Theory] Hypothesis Testing - An Overview.mp4	88.8 MB
10. [Theory] Types of Errors - Type I and Type II Errors.mp4	79.0 MB
3. [Theory] Central Limit Theorem.mp4	71.6 MB
2. [Theory] Population vs Samples.mp4	63.2 MB
14. [Theory] The p-Value.mp4	54.4 MB
7. [Theory] Statistical and Practical Significance.mp4	40.1 MB
8. [Theory] Null and Alternate Hypothesis.mp4	22.7 MB
6. [Theory] Basics of Hypothesis Testing.mp4	17.1 MB
/.../7. Hypothesis Testing Part 1 (One Sample Tests)/
5. One Sample Z Test - Examples.srt	6.8 KB
1.3 Section 7.ipynb	67.9 KB
2.1 Section 7.ipynb	67.9 KB
6. One Sample Z Test Using Python.srt	19.8 KB
9. [Theory] One Proportion Test.srt	16.1 KB
10. One Proportion Test Using Python.srt	15.2 KB
14. One Variance Test Using Python.srt	12.4 KB
7. One Sample t Test.srt	12.0 KB
2. [Theory] Tests for means, variances and proportions - Introduction.srt	11.3 KB
3. [Theory] One Sample Z Test - Conditions.srt	9.8 KB
12. [Theory] One Variance Test - Example 1.srt	9.4 KB
4. [Theory] One Sample Z Test.srt	8.8 KB
13. [Theory] One Variance Test - Example 2.srt	7.4 KB
8. One Sample t Test Using Python.srt	6.2 KB
1. Download Section 7 Resources.html	0.1 KB
11. [Theory] One Variance Test - Introduction.srt	5.1 KB
1.2 Smokers.csv	1.4 KB
10.1 Smokers.csv	1.4 KB
1.1 Machine1.csv	0.8 KB
6.1 Machine1.csv	0.8 KB
15. Quiz Hypothesis Testing Part 1.html	0.1 KB
2. [Theory] Tests for means, variances and proportions - Introduction.mp4	101.2 MB
9. [Theory] One Proportion Test.mp4	98.0 MB
6. One Sample Z Test Using Python.mp4	95.0 MB
4. [Theory] One Sample Z Test.mp4	87.4 MB
7. One Sample t Test.mp4	86.3 MB
10. One Proportion Test Using Python.mp4	85.6 MB
14. One Variance Test Using Python.mp4	72.8 MB
13. [Theory] One Variance Test - Example 2.mp4	65.8 MB
12. [Theory] One Variance Test - Example 1.mp4	55.9 MB
3. [Theory] One Sample Z Test - Conditions.mp4	52.5 MB
5. One Sample Z Test - Examples.mp4	51.9 MB
8. One Sample t Test Using Python.mp4	31.3 MB
11. [Theory] One Variance Test - Introduction.mp4	29.2 MB
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/2. Descriptive Statistics/
1. Download Section 2 Resources.html	0.1 KB
5. Quiz Descriptive Statistics.html	0.1 KB
7. Find the mean, mode, median and standard deviation.html	0.1 KB
8. Solution Find the mean, mode, median and standard deviation.html	0.2 KB
9. Find the Inter Quartile Range.html	0.1 KB
10. Solution Find the Inter Quartile Range.html	0.1 KB
6. Descriptive Statistics Using Python.srt	18.2 KB
1.1 Section 2.ipynb	12.0 KB
2. [Theory] Measurement of Central Tendency.srt	11.0 KB
3. [Theory] Measurement of Dispersion - Part 1.srt	9.0 KB
4. [Theory] Measurement of Dispersion - Part 2.srt	7.9 KB
6. Descriptive Statistics Using Python.mp4	89.3 MB
2. [Theory] Measurement of Central Tendency.mp4	83.9 MB
3. [Theory] Measurement of Dispersion - Part 1.mp4	65.6 MB
4. [Theory] Measurement of Dispersion - Part 2.mp4	51.3 MB
Total files 390