Learn · Introduction to Biostatistics
Lecture 6 of 40Week 2
Lecture 6: SME, Z-Score, Box plot
Prof. Shamik Sen · IIT Bombay
Credits and licence
- From
- Introduction to Biostatistics, IIT Bombay (at NPTEL)
- Licence
- CC BY-NC-SA, as NPTEL states it. Non-commercial use only.
- Attribution
- NPTEL states: "Distributed under Creative Commons Attribution-ShareAlike / CC BY - NC - SA", beside a BY-NC-SA badge.
- Who can watch
- Tweens profiles and older. How courses are placed
All the lectures
- Lecture 1: Introduction to the course
- Lecture 2: Data representation and plotting
- Lecture 3: Arithmetic mean
- Lecture 4: Geometric mean
- Lecture 5: Measure of Variability, Standard deviation
- Lecture 6: SME, Z-Score, Box plot
- Lecture 7: Moments, Skewness
- Lecture 8: Kurtosis, R programming
- Lecture 9: R programming
- Lecture 10: Correlation
- Lecture 11: Correlation and Regression
- Lecture 12: Correlation and Regression Part-II
- Lecture 13: Interpolation and extrapolation
- Lecture 14: Nonlinear data fitting
- Lecture 15: Concept of Probability: Introduction and basics
- Lecture 16: Counting principle, Permutations and Combinations
- Lecture 17: Conditional probability
- Lecture 18: Conditional probability and Random variables
- Lecture 19: Random variables, Probability mass function, and Probability density function
- Lecture 20: Expectation, Variance and Covariance
- Lecture 21: Expectation, Variance and Covariance Part - II
- Lecture 22: Binomial random variables and Moment generating function
- Lecture 23: Probability distribution: Poisson distribution and Uniform distribution Part-I
- Lecture 24: Uniform distribution Part-II and Normal distribution Part-I
- Lecture 25: Normal distribution Part-II and Exponential distribution
- Lecture 26: Sampling distributions and Central limit theorem Part-I
- Lecture 27: Sampling distributions and Central limit theorem Part-II
- Lecture 28: Central limit theorem Part-III and Sampling distributions of sample mean
- Lecture 29: Central limit theorem - IV and Confidence intervals
- Lecture 30: Confidence intervals Part-II
- Lecture 31: Test of Hypothesis - 1
- Lecture 32: Test of Hypothesis - 2 (1 tailed and 2 tailed Test of Hypothesis, p-value)
- Lecture 33: Test of Hypothesis - 3 (1 tailed and 2 tailed Test of Hypothesis, p-value)
- Lecture 34: Test of Hypothesis - 4 (Type - 1 and Type - 2 error)
- Lecture 35: T-test
- Lecture 36: 1 tailed and 2 tailed T-distribution, Chi-square test
- Lecture 37: ANOVA - 1
- Lecture 38: ANOVA - 2
- Lecture 39: ANOVA - 3
- Lecture 40: ANOVA for linear regression, Block Design