Introduction to Statistics: Descriptive Data Analysis

This is H
omepage
 for Introduction to Statistics Course. Descriptive Data Analysis is more than just manipulation of numbers, this course is designed to learn how to construct arguments using descriptive analysis, and avoid being deceived by statistics. 



Philosophy of the course is the LEARNING IS BY DOING. Accordingly, the students are EXPECTED to do a lot of work between classes. The principle of the "INVERTED CLASSROOM" which has proven extremely effective is followed. In the inverted classroom, lectures are delivered outside the class, while homework and discussion takes place inside class. 
For more about course see Description and Features of course.


 What to Learn
  1.  How there is no objectivity in statistical analysis; numbers and data are not objective facts.
  2.  How normative judgements can be introduced in Making Comparisons.
  3.  Understand that statistical analysis is crucially dependent on the real world.
  4. Only real world context allows us to differentiate between useful and useless knowledge. 
  5. Understanding the difference between relevant and useful statistical analysis, and irrelevant and dangerous types of analysis which lead to wrong and misleading conclusions. 
  6. Appropriate use of techniques for normal and non-normal data sets. 




 
 Institution   PIDE
 Duration16 Weeks
 Effort8 hours/week 
 Price Free
 Subject Introduction to Statistics
 Level Introductory
 Language English
 Video/Transcripts
 English

     
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ResourceActivityStatusDate
L00H Home Work - Pre-requisites for Course Activities to be done before start of main course Do at home March 29, 2017 
L01C First In Class Lecture Live Lecture by Dr. Asad Zaman on Nature of Course, Will describe nature and structure of course March 30, 2017 
L01H - View First Video Lecture on IntroStats Distinctive Features of Islamic Approach to Learning View Lecture, Do Quiz, at home, before next class April 3, 2017 
L02 C-Sorting, ranking First lecture on sorting, ranking and percentiles In class discussion on range min, max April 4, 2017 
L03H-Statistics as Rhetoric Spplementary Statistics As Rhetoric to be done at home, BEFORE next class April 5, 2017 
L04C-Percentrank & Percentiles Class lecture on Sorting & Ranking II Pecentrank and percentile meaning, use and calculation April 6, 2017 
L04H-Self learning Solve Quiz, Read Document on Percent Rank and Percentiles Do it before next class April 10, 2017 
L05 C-Lab Sorting Ranking & Percentiles Lab practice of computational concepts Extremely Important Staircase graph of Empirical CDF April 11, 2017 
L05H-Self learning Home ACtivity Index Number Arbitrary Ranking Read Malcolm Gladwell article April 12, 2017 
L06C-Index Numbers  Comparisons part 2: Index Numbers and Rankings In class lecture  April 13, 2017 
L06H-Indexing Notes on Indexing facts and fictions DIY quiz and video lecture April 17, 2017 
L07C-Lab on Laspayer & Paasch index Practice the index number calculation In class lab April 18, 2017 
L07H-Index numbers & Ranking Read articles on arbitrary Rankings Supplementary materials to understand rankings April 19, 2017 
L08C-Arbitrary Rankings In Class Lecture: Rankings: Arbitrary & Important Quiz, Lecture, Discussion,Group Activity, Feedback April 20, 2017 
L08H-Representing & Benchmarking Standard Statistical Measures of Central Tendency & their rhetorical usage  Home based learning unit April 24, 2017 
L09C-Representng & Benchmarking Reprenting and benchmarking by mean, median and mode Discussion on understanding the concepts April 25, 2017 
L09H-Lab on Mean, Median & Mode Mean, median & mode: Lab & computational quiz  Self learning of calculating & Interpreting Measures of Central Tendency  April 26, 2017 
L10C-In class Lab on calculation of Mean, Median and Mode Calculating & Interpreting Measures of Central Tendency  Teaching the computational skills required for this unit  April 27, 2017 
L10H-Measures of Dispersion Home Learning Unit - Video & Quiz  Do it before next class October 2, 2017 
L11C-Measures Of Spread & Variation Discussion on measures of spread and variation Class activity October 3, 2017 
L11H-Lab Measures of Dispersion EXCEL practice with IQR, SD, and other measures  Calculating, Understanding & Intepreting Spread  October 5, 2017 
L12C-Boxplot What is Boxplot and how to interpret it  Very useful tool for data distribution and spread  October 17, 2017 
L12H-Boxlot Practice What is Boxplot and how to interpret it  Very useful tool for data distribution and spread  October 18, 2017 
Data Visualization  Importance and Power of visualizing data Class Discussion October 30, 2017 
Showing 24 items
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