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Sampling - Coggle Diagram

- - - - a conclusion reached on the basis of evidence and reasoning.
      - drawing conclusions from your sample about your
        population
    - - applying your conclusions to populations other
        than the one you have studied
- - - - A 95% confidence interval (CI) is a range of values that is used to estimate an unknown population parameter, such as a population mean or proportion, with a certain level of confidence. In this case, the "95%" indicates that we are 95% confident that the interval contains the true population parameter. It is a way of expressing the uncertainty associated with a sample estimate.
      - Key terms
        
        Sample Mean - Represents the average value of the sample data, providing a central point around which the data is distributed.
        
        Sample Variance - Measures the variability or spread of the data points around the mean, indicating how dispersed the data points are. A larger variance indicates that the data points are more spread out from the mean, while a smaller variance indicates they are closer to the mean.
      - https://youtu.be/ENnlSlvQHO0?si=nVb-daFfhlzA6sv9
    - - Key terms
        
        The null hypothesis is a statement that there is no effect or no difference, and it serves as the default or starting assumption in hypothesis testing. It posits that any observed effect or difference in the sample data is due to random chance or variability and not due to a true effect.
        
        The alternative hypothesis is a statement that contradicts the null hypothesis. It suggests that there is an effect, a difference, or a relationship in the population, and it is not due to random chance. The alternative hypothesis represents what the researcher aims to prove or find evidence for.
      - https://youtu.be/Xni5YVlgiiQ?si=zCVCL2SIDTFBrJQr