| 1. Basic of Probability.mp4 | 164.7 MB | ||
| 1. Basic of Probability.srt | 38.9 KB | ||
| 1. Binomial distribution.mp4 | 71.2 MB | ||
| 1. Binomial distribution.srt | 16.7 KB | ||
| 1. Introduction.mp4 | 8 MB | ||
| 1. Introduction.srt | 1.1 KB | ||
| 1. Mean.mp4 | 49.1 MB | ||
| 1. Mean.srt | 10.2 KB | ||
| 1. Measures of Dispersion_variance_sd.mp4 | 123.1 MB | ||
| 1. Measures of Dispersion_variance_sd.srt | 25.6 KB | ||
| 1. Quartiles_quartile deviation.mp4 | 63.6 MB | ||
| 1. Quartiles_quartile deviation.srt | 16.1 KB | ||
| 1. Rates_Ratio_incidence_prevalence.mp4 | 227.8 MB | ||
| 1. Rates_Ratio_incidence_prevalence.srt | 36.4 KB | ||
| 1. Screening_test_confusion_matrix_1.mp4 | 126.2 MB | ||
| 1. Screening_test_confusion_matrix_1.srt | 18.8 KB | ||
| 1. correlation-coefficient.mp4 | 143 MB | ||
| 1. correlation-coefficient.srt | 26.3 KB | ||
| 1. normal_distribution.mp4 | 67.1 MB | ||
| 1. normal_distribution.srt | 9.8 KB | ||
| 1.1 5.5_notes_Correlation Analysis.pdf | 1.1 MB | ||
| 1.1 7.3-Discrete probability distribution-binomial-poisson.pdf | 186.1 KB | ||
| 1.2 7.4-binomila n poisson.xlsx | 11.8 KB | ||
| 2. Bayes theorem.mp4 | 130 MB | ||
| 2. Bayes theorem.srt | 32.6 KB | ||
| 2. Box plot.mp4 | 33.6 MB | ||
| 2. Box plot.srt | 11.5 KB | ||
| 2. Coefficient_variation_CV.mp4 | 60 MB | ||
| 2. Coefficient_variation_CV.srt | 10.8 KB | ||
| 2. Instructor.mp4 | 21.1 MB | ||
| 2. Instructor.srt | 2 KB | ||
| 2. Median.mp4 | 108.3 MB | ||
| 2. Median.srt | 19.4 KB | ||
| 2. Odds-Odd Ratio.mp4 | 101.8 MB | ||
| 2. Odds-Odd Ratio.srt | 15.1 KB | ||
| 2. Poisson distribution.mp4 | 63.1 MB | ||
| 2. Poisson distribution.srt | 15.6 KB | ||
| 2. Screening_test_confusion_matrix_2_details.mp4 | 113.1 MB | ||
| 2. Screening_test_confusion_matrix_2_details.srt | 17.1 KB | ||
| 2. correlation-Scatter-diagram.mp4 | 78.4 MB | ||
| 2. correlation-Scatter-diagram.srt | 22.1 KB | ||
| 2. normal_examples.mp4 | 196.2 MB | ||
| 2. normal_examples.srt | 32.5 KB | ||
| 2.1 3.3_Summary Measure- Measure of Dispersion.pdf | 740.2 KB | ||
| 2.1 6.3_notes_BasicProbabilities.pdf | 204.9 KB | ||
| 2.1 8.3-normal distribution with example.pdf | 1.4 MB | ||
| 2.1 9.4-Rates-Ratio-OR.pdf | 230.9 KB | ||
| 2.2 3.4_Problem_measure of dispersion.pdf | 56.3 KB | ||
| 2.2 6.4_notes_Bayes theorem.pdf | 170 KB | ||
| 2.2 8.4-Z-TABLE-STANDARD NORMAL PROBABILITY TABLE.pdf | 577.7 KB | ||
| 2.2 9.5-assignment.pdf | 260.6 KB | ||
| 2.3 6.5_Assignment_BasicProbabilities_Bayes theorem.pdf | 75.6 KB | ||
| 2.3 8.5-normal dist.xlsx | 9.8 KB | ||
| 3. Mode.mp4 | 82.2 MB | ||
| 3. Mode.srt | 16.6 KB | ||
| 3. Regression-analysis.mp4 | 67.4 MB | ||
| 3. Regression-analysis.srt | 9.8 KB | ||
| 3. Screening_test-example.mp4 | 147.6 MB | ||
| 3. Screening_test-example.srt | 29.3 KB | ||
| 3. Skewness_shape of the data.mp4 | 97.1 MB | ||
| 3. Skewness_shape of the data.srt | 18.1 KB | ||
| 3. What is Statistics.mp4 | 30.3 MB | ||
| 3. What is Statistics.srt | 5.8 KB | ||
| 3.1 1.3_what is statistics.pdf | 417.5 KB | ||
| 3.1 2.4_Summary Measures-Central tendency .pdf | 156.9 KB | ||
| 3.1 5.6_notes_regression .pdf | 801.6 KB | ||
| 3.2 2.5_problems.pdf | 52 KB | ||
| 4. Coefficient of Skewness.mp4 | 55.7 MB | ||
| 4. Coefficient of Skewness.srt | 12.4 KB | ||
| 4. Data.mp4 | 108.6 MB | ||
| 4. Data.srt | 18.6 KB | ||
| 4. Regression-example.mp4 | 175.5 MB | ||
| 4. Regression-example.srt | 39.1 KB | ||
| 4. Screening_test-bayes-theorem.mp4 | 79.9 MB | ||
| 4. Screening_test-bayes-theorem.srt | 11.4 KB | ||
| 4.1 1.4_about data.pdf | 732.6 KB | ||
| 4.1 5.7_assignment_problems-Correlation and Regression Analysis.pdf | 57.1 KB | ||
| 4.2 5.8-corr-reg-R.R | 10.2 KB | ||
| 4.3 5.9-corr-reg-cal.xlsx | 15.3 KB | ||
| Bonus Resources.txt | 409.6 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ▲ 81 total files | |||
Data science tools: Basic of Statistics
https://TutPig.com
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 29 lectures (7h) | Size: 2.8 GB
Introduction to statisrics and probability
What you'll learn
Students will be able to analyze, explain and interpret the data
They will understand the relationship and dependency between the data and how to make the prediction
Students will understand different method of data analyses such as measure of central tendency (mean, median, mode), measure of dispersion (variance, standar
Students will have basic understanding of probability and Bayes theorem
They will come to know about rates, ratio, odd ration and screening test
Requirements
No requirement is needed. students or anyone who are interested about data analyis can take the course
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