Advanced Statistical Methods
statistical-methods-for-data-science-2
Syllabus
Faculty: Dr.Banitamani Mallik
Course Name :Advanced Statistical Methods
Code(Credit) :CUTM1533(2-1-1)
• Ability to summarize and present data numerically and visually.
• Knowledge of which statistical methods to use in which situations
• Ability to think critically about data-based claims and quantitative arguments
• Ability to learn new statistical analysis techniques on your own
Upon successful completion of this course, students will be able to:
• Apply statistical methods and hypothesis testing to business problems
• Learn the details and complexities of Analysis of Variance (ANOVA)
• Learn some of the details and complexities of Multiple Regression (MR)
Module I: (2 hrs+0 hrs+2hr)
Statistics: Population, Sample, Sampling, Estimators and Estimates, Maximum Likelihood , Confidence Intervals
Project-1
Application of Confidence intervals as a tool in decision making
Module II: (3 hrs+0hr+2hr)
Hypothesis Testing: Null and the alternative hypothesis, Rejection region and significance level, Chi-Square Test
Project-2
Hypothesis Testing in Quality Management
Module III: (4 hrs+4 hrs+0hr)
Regression: Multiple Regression and Logistic Regression
Practice-1
Multiple Regression Analysis in Python
Practice-2
Logistic Regression using Python
Module IV: (3 hrs+4 hrs+2hr)
Analysis of Variance(ANOVA): F- Distribution, One way ANOVA, Two Way ANOVA
Practice-3
One way ANOVA using Python
Practice-4
Two way ANOVA using Python
Project-3
The utility of multivariate statistical techniques in hydro geochemical studies
Module V: (3 hrs+2 hrs+2hr)
Covariance: (ANCOVA): Analysis of Covariance (ANCOVA), Bivariate Pearson Correlation, Alternative Correlation Coefficients
Practice-5
Python Analysis of covariance (ANCOVA)
Project-4
Application of Analysis of covariance (ANCOVA) in psychological research
Module VI: (3 hrs+0hr+2hr)
Multivariate analysis of variance (MANOVA): One-way MANOVA, Two-way MANOVA
Project-5
Comparison of MANOVA to ANOVA Using an Example
Module VII: (3 hrs+2 hrs+2hr)
Time Series Analysis: Introducing Time Series Analysis, Components of Time Series Analysis, Multivariate Time Series Analysis
Practice-6
Time Series Analysis using Python
Project-6
A Report on Applications of Time Series Analysis in Census Analysis
Text Books:
1. Statistical Methods By S.P. Gupta (31st Edition) ; Publisher: Sultan Chand & Sons
2. Mathematical Statistics by S.C. Gupta & V.K. Kapur (10th Edition); Publisher: Sultan Chand & Sons.
Reference Books:
Understanding And Using Advanced Statistics by Jeremy Foster Emma Barkus Christian Yavorsky, SAGE Publications
Course outline Prepared by: Dr.Banitamani Mallik
Date: 18-06-2020
Source of reference: udemy, coursera, Harvard University
Note: 1 credit theory=10 hrs lecture, 1 credit practice/project=12.5 hrs lab/workshop/field work in a semester.
Population, Sample, Sampling, Estimators and Estimates
Web Link
https://www.youtube.com/watch?v=yx5KZi5QArQ
PPT1(Parameter Estimation)
Maximum likelihood, Confidence Intervals
Web Link
https://www.youtube.com/watch?v=tFWsuO9f74o
PPT2(Maximum Likelihood method )
Project-1
Application of Confidence intervals as a tool in Confidence Interval decision making
https://www.coursera.org/lecture/hypothesis-testing-confidence-intervals/application-of-confidence-interval-4UgKo
Project-1
Application of Confidence intervals as a tool in Confidence Interval decision making
Web Link
PPT3Confidence Interval
Null and the alternative hypothesis
Web Link
https://www.youtube.com/watch?v=ZzeXCKd5a18
Rejection region and significance level
Web Link
https://www.youtube.com/watch?v=BdeuCflLPQI
Chi-Square Test
Web Link
https://www.youtube.com/watch?v=2SKXRB-bJKo
Project-2
Hypothesis Testing in Quality Management
Web Link
Hypothesis Testing in Quality Management
Project-2
Hypothesis Testing in Quality Management
Web Link
https://www.youtube.com/watch?v=J9HPugGlcRI.
Multiple Regression
Web Link
https://www.youtube.com/watch?v=zITIFTsivN8
PPT4(Regression Analysis)Session 11Multiple Regression
Web Link
https://www.youtube.com/watch?v=K_EH2abOp00.
PPT5( Regression and Correlation Analysis )
Logistic Regression
Web Link
https://www.youtube.com/watch?v=yIYKR4sgzI8
Logistic Regression
Web Link
https://www.youtube.com/watch?v=yFKVI7vgPPs.
Practice-1
Multiple Regression Analysis in Python
Web Link
https://www.youtube.com/watch?v=M32ghIt1c88
Practice-1
Multiple Regression Analysis in Python
Web Link
https://www.youtube.com/watch?v=fJOhLKvWOJI.
Practice-2
Logistic Regression using Python
Web Link
https://www.youtube.com/watch?v=VCJdg7YBbAQ
Practice-2
Logistic Regression using Python
Web Link
https://www.youtube.com/watch?v=VK6v9Ure8Lk.
F- Distribution
Web Link
https://www.youtube.com/watch?v=w1TvaQgoNCY
One way ANOVA
Web Link
https://www.youtube.com/watch?v=rMnlVIkdukU
Two Way ANOVA
Web Link
https://www.youtube.com/watch?v=lZFmFuZGQTk
Practice-3
One way ANOVA using Python
Web Link
https://reneshbedre.github.io/blog/anova.html
Practice-3
One way ANOVA using Python
Web Link
https://www.youtube.com/watch?v=AhZ-hllEVxs.
Practice-4
Two way ANOVA using Python
Web Links
https://www.youtube.com/watch?v=T4IgVnmNH5A
https://raphaelvallat.com/pingouin.html
Practice-4
Two way ANOVA using Python
Web Links
https://www.youtube.com/watch?v=vvy_YRiEvpA.
Project-3
Application of Analysis of covariance (ANCOVA) in psychological research
Web Link
https://www.youtube.com/watch?v=LtdvDrZA4r0.
PPT6(Uses of regression and correlation analysis in bussines )
Application of Analysis of covariance (ANCOVA) in psychological research
Web Link
https://www.youtube.com/watch?v=_uYASFVUNpQ.
Analysis of Covariance (ANCOVA)
Web Link
https://www.youtube.com/watch?v=rpe4kPGteCQ
Bivariate Pearson Correlation
Web Link
https://www.youtube.com/watch?v=cagmwv4rMno
PPT7(SIMPLE LINEAR CORRELATION)
Alternative Correlation Coefficients
Web Link
https://www.youtube.com/watch?v=jmE1rfDjDGQ
Practice-5
Python Analysis of covariance (ANCOVA)
Web Link
https://www.youtube.com/watch?v=Kx6QhjGcjA0
Python Analysis of covariance (ANCOVA)
Web Link
https://www.youtube.com/watch?v=AhZ-hllEVxs.
Project-4
Application of Analysis of covariance (ANCOVA) in psychological research
Web Link
https://www.youtube.com/watch?v=a61mkzQRf6c.
Application of Analysis of covariance (ANCOVA) in psychological research
Web Link
https://www.youtube.com/watch?v=LtdvDrZA4r0.
One-way MANOVA
Web Link
https://www.youtube.com/watch?v=HdAwASZ7bNY
Two-way MANOVA
Web Link
https://www.youtube.com/watch?v=57do6ZVMp6Y
Two-way MANOVA
Web Link
https://www.youtube.com/watch?v=qM4-MrWeUnQ.
Project-5
Comparison of MANOVA to ANOVA Using an Example
Web Link
https://www.youtube.com/watch?v=jUksjmKvwos.
Project-5
Comparison of MANOVA to ANOVA Using an Example
Web Link
https://www.youtube.com/watch?v=Q116ZnLy5uA.
Introducing Time Series Analysis
Web Link
https://www.youtube.com/watch?v=GUq_tO2BjaU
Components of Time Series Analysis
Web Link
https://www.youtube.com/watch?v=e8Yw4alG16Q
Multivariate Time Series Analysis
Web Link
https://www.youtube.com/watch?v=3dvzReXBUMs
Practice-6
Time Series Analysis using Pandas
Web Link
https://www.youtube.com/watch?v=r0s4slGHwzE
Practice-6
Time Series Analysis using Pandas
Web Link
https://www.youtube.com/watch?v=0unf-C-pBYE.
Project-6
A Report on Applications of Time Series Analysis in Different Real Life Situations
Web Link
https://www.youtube.com/watch?v=wGUV_XqchbE.
Project-6
A Report on Applications of Time Series Analysis in Different Real Life Situations
Web Link
https://www.youtube.com/watch?v=m4b5yYx8oWw.
Course Name :Advanced Statistical Methods
Code(Credit) :CUTM1533(2-1-1)
Course Objectives
• Ability to summarize and present data numerically and visually.
• Knowledge of which statistical methods to use in which situations
• Ability to think critically about data-based claims and quantitative arguments
• Ability to learn new statistical analysis techniques on your own
Learning Outcomes
Upon successful completion of this course, students will be able to:
• Apply statistical methods and hypothesis testing to business problems
• Learn the details and complexities of Analysis of Variance (ANOVA)
• Learn some of the details and complexities of Multiple Regression (MR)
Course Syllabus
Module I: (2 hrs+0 hrs+2hr)
Statistics: Population, Sample, Sampling, Estimators and Estimates, Maximum Likelihood , Confidence Intervals
Project-1
Application of Confidence intervals as a tool in decision making
Module II: (3 hrs+0hr+2hr)
Hypothesis Testing: Null and the alternative hypothesis, Rejection region and significance level, Chi-Square Test
Project-2
Hypothesis Testing in Quality Management
Module III: (4 hrs+4 hrs+0hr)
Regression: Multiple Regression and Logistic Regression
Practice-1
Multiple Regression Analysis in Python
Practice-2
Logistic Regression using Python
Module IV: (3 hrs+4 hrs+2hr)
Analysis of Variance(ANOVA): F- Distribution, One way ANOVA, Two Way ANOVA
Practice-3
One way ANOVA using Python
Practice-4
Two way ANOVA using Python
Project-3
The utility of multivariate statistical techniques in hydro geochemical studies
Module V: (3 hrs+2 hrs+2hr)
Covariance: (ANCOVA): Analysis of Covariance (ANCOVA), Bivariate Pearson Correlation, Alternative Correlation Coefficients
Practice-5
Python Analysis of covariance (ANCOVA)
Project-4
Application of Analysis of covariance (ANCOVA) in psychological research
Module VI: (3 hrs+0hr+2hr)
Multivariate analysis of variance (MANOVA): One-way MANOVA, Two-way MANOVA
Project-5
Comparison of MANOVA to ANOVA Using an Example
Module VII: (3 hrs+2 hrs+2hr)
Time Series Analysis: Introducing Time Series Analysis, Components of Time Series Analysis, Multivariate Time Series Analysis
Practice-6
Time Series Analysis using Python
Project-6
A Report on Applications of Time Series Analysis in Census Analysis
Text Books:
1. Statistical Methods By S.P. Gupta (31st Edition) ; Publisher: Sultan Chand & Sons
2. Mathematical Statistics by S.C. Gupta & V.K. Kapur (10th Edition); Publisher: Sultan Chand & Sons.
Reference Books:
Understanding And Using Advanced Statistics by Jeremy Foster Emma Barkus Christian Yavorsky, SAGE Publications
Course outline Prepared by: Dr.Banitamani Mallik
Date: 18-06-2020
Source of reference: udemy, coursera, Harvard University
Note: 1 credit theory=10 hrs lecture, 1 credit practice/project=12.5 hrs lab/workshop/field work in a semester.
Session Plan
Session 1
Population, Sample, Sampling, Estimators and Estimates
Web Link
https://www.youtube.com/watch?v=yx5KZi5QArQ
PPT1(Parameter Estimation)
Session 2
Maximum likelihood, Confidence Intervals
Web Link
https://www.youtube.com/watch?v=tFWsuO9f74o
PPT2(Maximum Likelihood method )
Session 3
Project-1
Application of Confidence intervals as a tool in Confidence Interval decision making
https://www.coursera.org/lecture/hypothesis-testing-confidence-intervals/application-of-confidence-interval-4UgKo
Session 4
Project-1
Application of Confidence intervals as a tool in Confidence Interval decision making
Web Link
PPT3Confidence Interval
Session 5
Null and the alternative hypothesis
Web Link
https://www.youtube.com/watch?v=ZzeXCKd5a18
Session 6
Rejection region and significance level
Web Link
https://www.youtube.com/watch?v=BdeuCflLPQI
Session 7
Chi-Square Test
Web Link
https://www.youtube.com/watch?v=2SKXRB-bJKo
Session 8
Project-2
Hypothesis Testing in Quality Management
Web Link
Hypothesis Testing in Quality Management
Session 9
Project-2
Hypothesis Testing in Quality Management
Web Link
https://www.youtube.com/watch?v=J9HPugGlcRI.
Session 10
Multiple Regression
Web Link
https://www.youtube.com/watch?v=zITIFTsivN8
PPT4(Regression Analysis)Session 11Multiple Regression
Web Link
https://www.youtube.com/watch?v=K_EH2abOp00.
PPT5( Regression and Correlation Analysis )
Session 12
Logistic Regression
Web Link
https://www.youtube.com/watch?v=yIYKR4sgzI8
Session 13
Logistic Regression
Web Link
https://www.youtube.com/watch?v=yFKVI7vgPPs.
Session 14
Practice-1
Multiple Regression Analysis in Python
Web Link
https://www.youtube.com/watch?v=M32ghIt1c88
Session 15
Practice-1
Multiple Regression Analysis in Python
Web Link
https://www.youtube.com/watch?v=fJOhLKvWOJI.
Session 16
Practice-2
Logistic Regression using Python
Web Link
https://www.youtube.com/watch?v=VCJdg7YBbAQ
Session 17
Practice-2
Logistic Regression using Python
Web Link
https://www.youtube.com/watch?v=VK6v9Ure8Lk.
Session 18
F- Distribution
Web Link
https://www.youtube.com/watch?v=w1TvaQgoNCY
Session 19
One way ANOVA
Web Link
https://www.youtube.com/watch?v=rMnlVIkdukU
Session 20
Two Way ANOVA
Web Link
https://www.youtube.com/watch?v=lZFmFuZGQTk
Session 21
Practice-3
One way ANOVA using Python
Web Link
https://reneshbedre.github.io/blog/anova.html
Session 22
Practice-3
One way ANOVA using Python
Web Link
https://www.youtube.com/watch?v=AhZ-hllEVxs.
Session 23
Practice-4
Two way ANOVA using Python
Web Links
https://www.youtube.com/watch?v=T4IgVnmNH5A
https://raphaelvallat.com/pingouin.html
Session 24
Practice-4
Two way ANOVA using Python
Web Links
https://www.youtube.com/watch?v=vvy_YRiEvpA.
Session 25
Project-3
Application of Analysis of covariance (ANCOVA) in psychological research
Web Link
https://www.youtube.com/watch?v=LtdvDrZA4r0.
PPT6(Uses of regression and correlation analysis in bussines )
Session 26
Application of Analysis of covariance (ANCOVA) in psychological research
Web Link
https://www.youtube.com/watch?v=_uYASFVUNpQ.
Session 27
Analysis of Covariance (ANCOVA)
Web Link
https://www.youtube.com/watch?v=rpe4kPGteCQ
Session 28
Bivariate Pearson Correlation
Web Link
https://www.youtube.com/watch?v=cagmwv4rMno
PPT7(SIMPLE LINEAR CORRELATION)
Session 29
Alternative Correlation Coefficients
Web Link
https://www.youtube.com/watch?v=jmE1rfDjDGQ
Session 30
Practice-5
Python Analysis of covariance (ANCOVA)
Web Link
https://www.youtube.com/watch?v=Kx6QhjGcjA0
Session 31
Python Analysis of covariance (ANCOVA)
Web Link
https://www.youtube.com/watch?v=AhZ-hllEVxs.
Session 32
Project-4
Application of Analysis of covariance (ANCOVA) in psychological research
Web Link
https://www.youtube.com/watch?v=a61mkzQRf6c.
Session 33
Application of Analysis of covariance (ANCOVA) in psychological research
Web Link
https://www.youtube.com/watch?v=LtdvDrZA4r0.
Session 34
One-way MANOVA
Web Link
https://www.youtube.com/watch?v=HdAwASZ7bNY
Session 35
Two-way MANOVA
Web Link
https://www.youtube.com/watch?v=57do6ZVMp6Y
Session 36
Two-way MANOVA
Web Link
https://www.youtube.com/watch?v=qM4-MrWeUnQ.
Session 37
Project-5
Comparison of MANOVA to ANOVA Using an Example
Web Link
https://www.youtube.com/watch?v=jUksjmKvwos.
Session 38
Project-5
Comparison of MANOVA to ANOVA Using an Example
Web Link
https://www.youtube.com/watch?v=Q116ZnLy5uA.
Session 39
Introducing Time Series Analysis
Web Link
https://www.youtube.com/watch?v=GUq_tO2BjaU
Session 40
Components of Time Series Analysis
Web Link
https://www.youtube.com/watch?v=e8Yw4alG16Q
Session 41
Multivariate Time Series Analysis
Web Link
https://www.youtube.com/watch?v=3dvzReXBUMs
Session 42
Practice-6
Time Series Analysis using Pandas
Web Link
https://www.youtube.com/watch?v=r0s4slGHwzE
Session 43
Practice-6
Time Series Analysis using Pandas
Web Link
https://www.youtube.com/watch?v=0unf-C-pBYE.
Session 44
Project-6
A Report on Applications of Time Series Analysis in Different Real Life Situations
Web Link
https://www.youtube.com/watch?v=wGUV_XqchbE.
Session 45
Project-6
A Report on Applications of Time Series Analysis in Different Real Life Situations
Web Link
https://www.youtube.com/watch?v=m4b5yYx8oWw.
Course Materials
Session plan & materials
No materials published yet.