Visualizations can really help people understand hypothesis testing. They make tricky ideas easier to see and understand.

1. Null and Alternative Hypotheses: A simple diagram that shows the null hypothesis (we call it $H_0$) next to the alternative hypothesis (called $H_1$) helps students see what each one means.

2. Type I and Type II Errors: Using pictures like Venn diagrams can show where Type I errors (these are false positives) and Type II errors (these are false negatives) happen. This makes these ideas easier to understand.

3. Significance Levels: Graphs that show important areas help explain how significance levels work. Usually, we set the significance level at $\alpha = 0.05$. This level helps us decide when to reject $H_0$.

4. P-values: We can use a shaded area under a curve to show what a p-value is and how it helps in making decisions. This also helps people see how it compares to the significance level.

Overall, these tools make hypothesis testing less confusing. They help students connect what they learn in theory with real-life examples.