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t statistics, Correlation, Hypothesis Test t Statistic - Coggle Diagram

- - - - positive correlation- The second stage of the process is to determine whether the effect is large enough to be significant.
      - negative correlation- the two variables tend to go in opposite directions. As the X variable increases, the Y variable decreases. That is, it is an inverse relationship.
- - - - Used when X and Y values are ranks
      - Used when a researcher wants to measure the consistency of a relationship between X and Y
      - Ranking tiered scores
        
        List the scores in order from smallest to largest. Include tied values in the list.
        
        Assign a rank (first, second, etc.) to each position in the ordered list.
        
        When two (or more) scores are tied, compute the mean of their ranked positions, and assign this mean value as the final rank for each score
    - - variable with only two values is called a dichotomous variable or a binomial variable
      - examples: male/female, true/false, etc.
      - the correlation measures the strength and significance of the relationship between two variables
    - - computed via a 2-step procedure
      - Convert each of the dichotomous variables to numerical values by assigning a 0 to one category and a 1 to the other category for each of the variables
      - Use the regular Pearson formula with the converted scores.
- - - - Find the X deviation and the Y deviation for each individual.
      - Find the product of the deviations for each individual.
      - Add the products.
- - - - a. calculate the sample variance
      - b. use the sample variance and the sample size to compute the estimated standard error.
      - c. compute the t statistic