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Hypothesis Testing - Coggle Diagram

- - - - Null hypothesis is created first and states that the treatment has no effect.
      - The alternative hypothesis is created after and states that the treatment did have an effect. In other words, the independent variable did effect the dependent variable.
    - - Determine which sample means are consistent with the null hypothesis and which sample means are at odds with the hypothesis. Sample means are then divided into two categories: sample means close to the null and sample means far from the null.
        
        Area of critical region in tails is determined by the alpha level. If data falls within this region, the null hypothesis is rejected.
        
        Defined using level of significance, or alpha level. This is used to find the low probability samples. Typically .05 (5%) or .01 (1%).
    - - Collect raw data and summarize into appropriate statistics.
      - Comparison can be made by computing z-score to compare location of sample mean to the hypothesized population mean.
        
        Calculate using formula:
    - - Using the obtained z-score, make a decision regarding the null hypothesis. There are only two types of outcomes.
        
        The sample data are located in the critical region which indicates a very unlikely score and will lead to a rejection of the null hypothesis.
        
        2.The sample data are not located in the critical region which means the mean is reasonably close to the population mean. This leads to the failure to reject the null hypothesis.
- - - - It is assumed that the standard deviation for the unknown population is the same as it was for the population before treatment.
        
        We will be able to use the Unit Normal Table because the distribution will be normally shaped.