TU-L0022 - Statistical Research Methods D, 13.01.2021-07.04.2021

Topic outline

• Unit 2: Causal inference and basics of linear regression model
  To complete this unit you need to

  1. Watch the video lectures
  2. Read the materials for the written assignment 1 (mandatory)
  3. Complete the unit 2 discussion forum task
  4. Return written assignment 1 (mandatory)
  5. View the model answer for written assignment 1 and instructor's comments to written assignment 1 (mandatory)
  6. Start working on data analysis assignment 1 (mandatory)
  7. Participate in the seminar (mandatory)
  8. Participate in the computer class (optional)
  9. Submit reflection and feedback for unit 2

  The unit introduces the principles of causal inference and basics of linear regression models. After this unit, you should

  1. Understand the three conditions for causality and why you cannot Interpret regression results as evidence of causality unless the regression is used as a part of a research design that takes the temporal order of cause and effect into account and more importantly eliminates rival explanations.
  2. Understand that regression (and other analysis results) need to be interpreted and explained to a reader in a way that makes then understandable for people that do not know statistical analysis very well. You should also know that p-value is not the main result but simply indicates which regression coefficients you should probably pay more attention to when interpreting the results.
  3. Understand that statistical analysis is not rocket science, but a collection of fairly intuitive ideas and simple mathematics. (If you go beyond regression, then the math can get a bit more complicated.)

  • Select activity Unit 2 discussion forum

    

    Unit 2 discussion forum

    Completion

    Students must

    

    Make forum posts: 1

    

    Receive a grade
  • Select activity Video lectures

    Video lectures

  • Select activity Topic 1: Introduction

    Topic 1: Introduction
    

  • Select activity Introduction to quantitative research (7:39)

    

    Introduction to quantitative research (7:39) Interactive Content

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    Receive a grade
  • Select activity Topic 2: Basic statistics

    Topic 2: Basic statistics

  • Select activity Uses of statistics (4:41)

    

    Uses of statistics (4:41) Interactive Content

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  • Select activity Relationship between theory and data (21:34)

    

    Relationship between theory and data (21:34) Interactive Content

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  • Select activity Basic descriptive statistics (14:27)

    

    Basic descriptive statistics (14:27) Interactive Content

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  • Select activity Population, sample , estimate, and standard error (21:47)

    

    Population, sample , estimate, and standard error (21:47) Interactive Content

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  • Select activity Sampling and sample selection (21:05)

    

    Sampling and sample selection (21:05) Interactive Content

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  • Select activity Topic 3: Statistical inference

    Topic 3: Statistical inference

  • Select activity Rauser (2014) "Statistics without the agonizing pain" (11:48)

    

    Rauser (2014) "Statistics without the agonizing pain" (11:48) Interactive Content

    Completion

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    Receive a grade

    Rauser, J. (2014, October 15). Statistics Without the Agonizing Pain. Presented at the Big Data Conference - Strata + Hadoop World, New York, NY. Retrieved from http://strataconf.com/stratany2014/public/schedule/detail/37554
    

  • Select activity Statistical inference (12:38)

    

    Statistical inference (12:38) Interactive Content

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    Receive a grade
  • Select activity Null hypothesis significance testing (NHST) (12:38)

    

    Null hypothesis significance testing (NHST) (12:38) Interactive Content

    Completion

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    Receive a grade
  • Select activity Confidence intervals (6:45)

    

    Confidence intervals (6:45) Interactive Content

    Completion

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    Receive a grade
  • Select activity Topic 4: Causal inference

    Topic 4: Causal inference

  • Select activity Causal inference (9:35)

    

    Causal inference (9:35) Interactive Content

    Completion

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    Receive a grade
  • Select activity Randomized experiments (6:45)

    

    Randomized experiments (6:45) Interactive Content

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  • Select activity Statistical controls (11:40)

    

    Statistical controls (11:40) Interactive Content

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  • Select activity Topic 5: Regression analysis

    Topic 5: Regression analysis

  • Select activity Idea of regression analysis (8:33)

    

    Idea of regression analysis (8:33) Interactive Content

    Completion

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    Receive a grade
  • Select activity Regression estimation (7:11)

    

    Regression estimation (7:11) Interactive Content

    Completion

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  • Select activity Interpretation of regression results (25:12)

    

    Interpretation of regression results (25:12) Interactive Content

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  • Select activity Regression example with R (15:03)

    

    Regression example with R (15:03) Interactive Content

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  • Select activity Topic 6: Quality of quantitative research

    Topic 6: Quality of quantitative research

  • Select activity Quality of quantitative research (7:49)

    

    Quality of quantitative research (7:49) Interactive Content

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    Receive a grade
  • Select activity Assignments and model answersModel answers are sho...

    Assignments and model answers

    Model answers are shown only to students whose assignments have been graded.

  • Select activity Written assignment 1 (mandatory)

    

    Written assignment 1 (mandatory) Turnitin Assignment 2

    Completion

    Students must

    

    View

    

    Receive a grade
  • Select activity Data analysis assignment 1 (mandatory)

    

    Data analysis assignment 1 (mandatory) URL

    Data analysis assignment 1 (mandatory) is submitted to Unit 3.
    

  • Select activity Screencasts for data analysis assignment 1

    

    Screencasts for data analysis assignment 1 URL

    Screencasts for data analysis assignment 1 are located in Unit 3.

  • Select activity Reflection and feedback Unit 2Reflection is a key ...

    Reflection and feedback Unit 2

    Reflection is a key element of learning. At the end of the unit it is good time to look back at what you have learned, where you did well, and what you can still improve on. After you have completed all parts of the unit and received grades and feedback for all your submitted work, will in a short feedback form below.

  • Select activity Materials

    Materials

  • Select activity Unit 2 slides

    

    Unit 2 slides File PPTX
  • Select activity Regression models with excel

    

    Regression models with excel File XLSX
  • Select activity Screencasts for excel exercise

    

    Screencasts for excel exercise Page
  • Select activity Additional resources

    Additional resources

  • Select activity Stata YouTube channel

    

    Stata YouTube channel Page

    Videos from Stata YouTube channel that are relevant for the first the data analysis assignment.
    

  • Select activity Flinga Wall: Questions

    

    Flinga Wall: Questions URL
  • Select activity Flinga board 1: Unit overview

    

    Flinga board 1: Unit overview URL
  • Select activity Flinga board 2: Heckman paper

    

    Flinga board 2: Heckman paper URL
  • Select activity Flinga board 3: Research design

    

    Flinga board 3: Research design URL