Zenler Player
Your course is loading. Hang tight.
Statistics with Python (In Progress)
Back to curriculum
0% Complete
0% Complete
Quiz - Prerequisites
Untitled lesson
Module 1 Slides
1. Outline of topics in this course
2. Why learn statistics?
3. Examples of use of statistics
4. How exactly is statistics use?
5. Data literacy and its importance
6. What you will get out of this course
Module 2 Slides
1. Learning objective
2. Example of environmental impact assessment
3. Statistical studies: Observational and Experimental
4. Observational study
5. Experimental study
6. Cohort study
7. Institutional data and retrospective cohort study
8. Cross-sectional study
9. Ecological study
10. Summary: Statistical studies
11. Data collection: population and sample
12. Review of key concepts in data collection
Quiz (Module 2)
Module 3.1 Slides
Module 3 Google Colab Notebook
1. Module objective and motivation
2. Three things to consider for a graphical summary
3. Choosing appropriate graphical display
4. Displaying categorical data - bar plot
5. Displaying categorical data- comparative bar plot
6. Solutions: Tech layoff data
Quiz (Barplot): Did you notice the difference in two barplots?
7. Why is histogram so important?
8. Understanding histogram interactively
9. Barplot vs histogram
10. Clarifying the histogram of nosie-level example
11. Frequency, relative frequency and density histograms
12. Clearly understanding density histogram (TO BE POSTED)
13. Quick recap of histogram
14. Exercise: Draw and interpret a histogram
15.1 More on Density Histogram
15.2 Shape of a histogram
15.3 Concept of density (interactive app)
16.1 Scatterplot intuition through examples
16.2 What is a scatterplot
16.3 Scatterplot Matrix
17. Project on Scatterplot
18. Time Series plot (includes Exercise)
1. Module Intro (topics, goals)
2. Building intuition of location and spread of a distribution
3. Variability and its measures
4. Building intuition to measure variability
5. How to measure total variability
6. What central value to use?
7. How to calculate variance
8. Standard Deviation (SD)
9. Range as a messure of variability
10. Quantiles (Quartile, Percentile)
11. Five-number Summary (Box plot)
Really? Yup.
Getting better
Feeling good about probability :-)
Don't lie to me - its not random
I am about to fit
Normal distribution is not so normal- everyone lied :-(
Okay, I am getting it now
Love it or hate it: p-value is everywhere
Its so complicated!
I now understand it - p-value is easy peasy !!!
Why did everyone make it so complicated ??
p-value is the easiest thing to understand-- statistics is beautiful! OMG
Now I know why everyone uses regression
Simple Linear Regression
Multiple Linear Regression
Binary Logistic Regression
Once you're done here, move on to Machine Learning 360 course
START HERE
Quiz - Prerequisites
Untitled lesson
Module 1: Why Statistics?
Module 1 Slides
1. Outline of topics in this course
Preview
2. Why learn statistics?
Preview
3. Examples of use of statistics
Preview
4. How exactly is statistics use?
Preview
5. Data literacy and its importance
Preview
6. What you will get out of this course
Preview
Module 2: Getting Data
Module 2 Slides
1. Learning objective
2. Example of environmental impact assessment
3. Statistical studies: Observational and Experimental
4. Observational study
5. Experimental study
6. Cohort study
7. Institutional data and retrospective cohort study
8. Cross-sectional study
9. Ecological study
10. Summary: Statistical studies
11. Data collection: population and sample
12. Review of key concepts in data collection
Quiz (Module 2)
Module 3.1: Describing Data Distribution: Graphical Methods (In Progress)
Module 3.1 Slides
Module 3 Google Colab Notebook
1. Module objective and motivation
2. Three things to consider for a graphical summary
3. Choosing appropriate graphical display
4. Displaying categorical data - bar plot
5. Displaying categorical data- comparative bar plot
6. Solutions: Tech layoff data
Quiz (Barplot): Did you notice the difference in two barplots?
7. Why is histogram so important?
8. Understanding histogram interactively
9. Barplot vs histogram
10. Clarifying the histogram of nosie-level example
11. Frequency, relative frequency and density histograms
12. Clearly understanding density histogram (TO BE POSTED)
13. Quick recap of histogram
14. Exercise: Draw and interpret a histogram
15.1 More on Density Histogram
15.2 Shape of a histogram
15.3 Concept of density (interactive app)
16.1 Scatterplot intuition through examples
16.2 What is a scatterplot
16.3 Scatterplot Matrix
17. Project on Scatterplot
18. Time Series plot (includes Exercise)
Module 3.2: Describing Data Distribution - Numerical Methods (In progress)
1. Module Intro (topics, goals)
2. Building intuition of location and spread of a distribution
3. Variability and its measures
4. Building intuition to measure variability
5. How to measure total variability
6. What central value to use?
7. How to calculate variance
8. Standard Deviation (SD)
9. Range as a messure of variability
10. Quantiles (Quartile, Percentile)
11. Five-number Summary (Box plot)
Crying with Probability (Not yet started)
Really? Yup.
Getting better
Feeling good about probability :-)
OMG - Random Variables! (Not yet started)
Don't lie to me - its not random
Pulling my hair - Probability Distribution (Not yet started)
I am about to fit
Normal distribution is not so normal- everyone lied :-(
Okay, I am getting it now
Getting totally lost with Hypothesis testing (Not yet started)
Love it or hate it: p-value is everywhere
Its so complicated!
I now understand it - p-value is easy peasy !!!
Why did everyone make it so complicated ??
p-value is the easiest thing to understand-- statistics is beautiful! OMG
Relationship between Many Variables (Not yet started)
Now I know why everyone uses regression
Simple Linear Regression
Multiple Linear Regression
Binary Logistic Regression
Next Course --> Machine Learning
Once you're done here, move on to Machine Learning 360 course
×
This is an unpublished lesson. This lesson will not be shown for students unless you set it as Public.
Back to Dashboard
No contents are available in this lesson!
No lessons available !
Back to Dashboard
Lesson contents locked
Enroll to unlock this lesson.
Enroll to unlock
Mark as Complete