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picture1_Chi Square Test Ppt 69598 | Si0030 Lecture 5 Quantitative Data Analysis I P Values Chi Square And T Tests


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File: Chi Square Test Ppt 69598 | Si0030 Lecture 5 Quantitative Data Analysis I P Values Chi Square And T Tests
introduction introduction formulating hypotheses selecting statistical tests understanding probability p values chi square test for independence independent samples t test paired samples t test formulating hypotheses i formulating hypotheses i ...

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              Introduction
              Introduction
   • Formulating Hypotheses
   • Selecting Statistical Tests
   • Understanding Probability (‘p’ values)
   • Chi-Square Test for Independence
   • Independent Samples t-Test
   • Paired Samples t-Test
       Formulating Hypotheses I
       Formulating Hypotheses I
   • In Social Science we use the ‘Scientific Method’:
    –Formulate hypotheses
    –Collect data
    –Test hypotheses
    –Interpret results
   • To formulate a hypothesis:
    –Reasonable justification for relationship
    –Past research or observation
    –Must be disprovable (Popper’s Falsification Theory)
          Dependent variable (x) can be predicted through 
          Dependent variable (x) can be predicted through 
               independent variable (y)
               independent variable (y)
         Formulating Hypotheses II
         Formulating Hypotheses II
   • H  = The Null Hypothesis
      0
     –No relationship exists between dependent and independent 
      variables
     –e.g. there is no relationship between income and age
   • H  = The Alternative Hypothesis
      1
     –Some relationship exists between dependent and 
      independent variables
     –e.g. there is a relationship between income and age
               How do we test hypotheses?
               How do we test hypotheses?
                    Selecting Statistical Tests
                    Selecting Statistical Tests
                            Remember the levels of measurement (week 1)!
                            Remember the levels of measurement (week 1)!
     Dependent  Independen
      Variable    t Variable (x)   Test to Use          Example                   Notes
         (y)
    Nominal or  Nominal or       Chi-square       Skateboard            Expected frequency 
    Ordinal       Ordinal        test for         ownership (y) and     must not be lower than 
                                 independence Sex (x)                   5 in any cell
    Interval      Nominal or     t-test (paired   Income (y) and Sex    Ideally you need 50 in 
                  Ordinal        or               (x)                   each of the groups that 
                                 independent                            you are comparing
                                 samples)
    Interval      Interval       Correlation      Income (y) and Age  Relationship must be 
                                 Regression       (x)                   linear
                       Note the relationship between dependent and independent
                       Note the relationship between dependent and independent
     Understanding Probability I
     Understanding Probability I
  • Where does probability come into this?
  • We use statistical tests to assess whether the 
   hypothesised differences exist and whether they are 
   ‘genuine’ or due to ‘random chance’
  • e.g. how confident can we be that any difference between 
   male and female salaries is not simply a coincidence?
  • Remember last week – samples and populations!
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...Introduction formulating hypotheses selecting statistical tests understanding probability p values chi square test for independence independent samples t paired i in social science we use the scientific method formulate collect data interpret results to a hypothesis reasonable justification relationship past research or observation must be disprovable popper s falsification theory dependent variable x can predicted through y ii h null no exists between and variables e g there is income age alternative some how do remember levels of measurement week independen example notes nominal skateboard expected frequency ordinal ownership not lower than sex any cell interval ideally you need each groups that are comparing correlation regression linear note where does come into this assess whether hypothesised differences exist they genuine due random chance confident difference male female salaries simply coincidence last populations...

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