# How to Do a Hypothesis Test in the TI 84 for a Single Percentage | Summary and Q&A

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February 18, 2020
by
The Math Sorcerer
How to Do a Hypothesis Test in the TI 84 for a Single Percentage

## TL;DR

This video explains how to conduct a hypothesis test for a single proportion using a TI-84 calculator.

## Key Insights

• 🔂 Hypothesis testing for a single proportion involves comparing a sample proportion to a predetermined population proportion.
• 🏆 The TI-84 calculator provides a convenient tool for performing hypothesis tests for single proportions.
• 🟰 The null hypothesis assumes that the population proportion is equal to a specified value, while the alternative hypothesis considers other possible values.
• 🆘 The p-value helps determine the strength of evidence against the null hypothesis, with a larger p-value indicating weaker evidence.
• 💁 The choice of alternative hypothesis (greater than, less than, or not equal to) depends on the research question and the information provided.
• 🥺 The sample size plays a critical role in the accuracy of the hypothesis test, with larger sample sizes often leading to more reliable conclusions.
• 🎚️ Significance levels, such as alpha, are typically selected based on the desired level of confidence in the test results.

## Transcript

hi everyone in this video I'm going to show you how to do a hypothesis test for one percentage in other words a hypothesis test for a single proportion using the ti-84 calculator so let's briefly read the question and then we'll go into the calculator so a study reported that 47% of people who live in Ireland believe in leprechauns Wilson sampled o... Read More

### Q: What is the purpose of conducting a hypothesis test for a single proportion?

The purpose of this test is to determine if a sample proportion provides sufficient evidence to support or reject a claim about the population proportion.

### Q: How is the p-value interpreted in a hypothesis test?

The p-value represents the probability of obtaining a sample proportion as extreme as the observed proportion, assuming the null hypothesis is true. If the p-value is less than the significance level, the null hypothesis is rejected.

### Q: What is the significance level in a hypothesis test?

The significance level, denoted as alpha, is a pre-determined threshold used to determine whether the null hypothesis should be rejected. It represents the probability of incorrectly rejecting the null hypothesis.

### Q: What does it mean if the p-value is greater than the significance level?

If the p-value is greater than the significance level, there is not enough evidence to reject the null hypothesis. It suggests that the observed sample results are likely due to random chance.

## Summary & Key Takeaways

• The video demonstrates how to perform a hypothesis test for a single proportion using the TI-84 calculator.

• A study suggests that 47% of people in Ireland believe in leprechauns, and the question is whether a sample of 1,006 people supports this percentage.

• The calculation involves entering the null hypothesis, the number of successes, the sample size, and the alternative hypothesis, and then comparing the calculated p-value with the significance level (alpha).