Read the summary and the most important questions on Statistics & Methodology

• Lecture 1

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• What is a test statistic?

  Just an arbitrary number. We need to compare this statistic to some objective reference.

• What does the area under the curve represent?

  The probability of observing a test statistic within the corresponding interval. If it is in the tales, then it is unlikely to be true.

• t = 1.86 and the p = 0.032. Formulate the sentence of probability.

  There is a 0.032 probability of observing a test statistic at least as large as t , if the H0 is true.

• What is statistical modeling?

  Put the interesting parts into a mathematical representation and 'ignore' the uninteresting parts

• Lecture 2

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• What are the three steps when operationalizing research questions?

  1. Make sure you understand exactly what is being asked.
     
  2. Make questions rigorous and quantifiable
     
  3. If possible, code the research question into hypothesis.
     

• What are EDA and CDA?

  • Exploratory data analysis
  • Interactively analyze or explore your data.
  • Confirmatory data analysis
  • Evaluate your evidence

  
  
  They can both stand alone. 
  

  • When the data is well understood, we can proceed directly to CDA. 
    
  • If we don't care about testing hypotheses, we can focus on EDA.
    

• Three important things when screening or cleaning data?Look for:

  1. Missing data
     
  2. Univariate outliers
  3. Invalid values

• EDA can be used to sanity check hypotheses.What should happen with a hypothesis that fails a sanity check?

  Treated as rejected.

• Lecture 3

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• R = an N x P pattern matrix encoding non-response. It consists of?

  Just 0's and 1's. Where 1 is observing a value and 0 is a missing value.

• What do missing data (or response) patterns represent?

  They represent unique combinations of observed and missing items.