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Introduction to Biostatistics

-statistics are simply a collection of tools that researchers employ to help answer research questions

    INFERENTIAL STATISTICS: COMMON TESTS

    Chi-Squire Tests

    • Chi-square test is an inferential statistics technique designed to test for significant relationships between two variables organized in a bivariate table.
    • Chi-square requires no assumptions about the shape of the population distribution from which a sample is drawn. However, like all inferential techniques it assumes random sampling.
    • It can be applied to variables measured at a nominal and/or an ordinal level of measurement.
    • The research hypothesis (H1) proposes that the two variables are related in the population.
    • The null hypothesis (H0) states that no association exists between the two cross-tabulated variables in the population, and therefore the variables are statistically independent.

Formula for computing chi-squire statistic

chi-squire formula

Where, O=observed frequency, and  E = expected frequency

  • The essence of the chi squire test is to compare the observed frequencies with the frequencies expected for independence
    • if the difference between observed and expected frequencies is large, then we can reject the null hypothesis of independence.
  • Determining the Degrees of Freedom

df = (r – 1)(c – 1)
where, r = the number of rows and c = the number of columns

 

 
     
   
   
 
           
 

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