Final Answer:
The purpose of a 1-Sample Null Hypothesis Significance Test (NHST) is to determine whether there is significant evidence to reject the null hypothesis, which typically states that there is no significant difference between a sample's mean and a known or hypothesized population mean.
Step-by-step explanation:
The purpose of a 1-Sample Null Hypothesis Significance Test (NHST) is to assess whether the mean of a single sample is significantly different from a hypothesized population mean. This test is commonly used in research to determine if there is enough evidence to reject the null hypothesis, which posits that there is no significant difference.
For a 1-Sample NHST when the sample size (n) is greater than 30 and the response variable is continuous, the critical value can be determined using a standard normal distribution. The critical value (z) is obtained based on the desired level of significance (α) and is compared to the calculated test statistic.
For n < 30 with a continuous response variable, the critical value is determined using Student's t-distribution with n-1 degrees of freedom.
When n > 30 and the response variable is binary (proportional), the critical value is often determined using the standard normal distribution for large sample sizes.
The formulas for critical values involve looking up the corresponding values from the standard normal or t-distribution tables based on the chosen significance level. These critical values serve as thresholds for deciding whether to reject the null hypothesis based on the calculated test statistic.