Here are the essential concepts you must grasp in order to answer the question correctly.
Null Hypothesis
The null hypothesis is a statement that there is no effect or no difference, and it serves as the default assumption in hypothesis testing. Researchers aim to gather evidence against the null hypothesis to support an alternative hypothesis. In this context, rejecting the null hypothesis indicates that the observed data is statistically significant.
Recommended video:
t-Distribution
The t-distribution is a type of probability distribution that is symmetric and bell-shaped, similar to the normal distribution but with heavier tails. It is used in hypothesis testing, particularly when sample sizes are small or when the population standard deviation is unknown. The shape of the t-distribution changes with the degrees of freedom, affecting the critical values for hypothesis testing.
Recommended video:
Critical Values: t-Distribution
Critical Value and Rejection Region
The critical value is a threshold that determines the boundary for rejecting the null hypothesis in hypothesis testing. The rejection region is the area in the tails of the distribution where, if the test statistic falls, the null hypothesis can be rejected. In the provided graph, the shaded area indicates the rejection region, and the position of the test statistic t = 1.4 relative to this region is crucial for making a decision about the null hypothesis.
Recommended video:
Critical Values: t-Distribution