yego.me
💡 Stop wasting time. Read Youtube instead of watch. Download Chrome Extension

Conclusion for a two-sample t test using a P-value | AP Statistics | Khan Academy


2m read
·Nov 11, 2024

A sociologist studying fertility in France and Switzerland wanted to test if there was a difference in the average number of babies women in each country have. The sociologists obtained a random sample of women from each country. Here are the results of their test:

You can see a hundred percent sample from France, 100 sample from Switzerland. They actually don't have to be the same sample size. We have our sample means, our sample standard deviations. You have the standard error of the mean, which for each sample would be our estimate of the standard deviation of the sampling distribution of the sample mean.

And here it says t-test for the means of these different populations being different. Just to make sure we can make sense of this, let's just remind ourselves what's going on. The null hypothesis is that there's no difference in the mean number of babies that women in France have versus the mean number of babies that women in Switzerland have. That would be our null hypothesis—the no news here hypothesis.

Our alternative would be that they are different, and that's what we have right over here. It's a t-test to see if we have evidence that would suggest our alternative hypothesis. What we do is we assume the null hypothesis. From that, you're able to calculate a t statistic, and then from that t statistic and the degrees of freedom, you are able to calculate a p-value.

If that p-value is below your significance level, then you say, "Hey, this was a pretty unlikely scenario. Let me reject the null hypothesis," which would suggest the alternative. But if your p-value is greater than your significance level, then you would fail to reject your null hypothesis, and so you would not have sufficient evidence to conclude the alternative.

So what's going on over here? You really just have to compare this value to this value. It says, "At the alpha is equal to 0.05 level of significance, is there sufficient evidence to conclude that there is a difference in the average number of babies women in each country have?" Well, we can see that our p-value, 0.13, is greater than our alpha value, 0.05.

Because of that, we fail to reject our null hypothesis. To answer their question, no, there is not sufficient evidence to conclude that there is a difference. There is not sufficient evidence to reject the null hypothesis and suggest the alternative.

More Articles

View All
Sports Betting Is Destroying Young Men
In May of 2023, Ivan Tony, an English soccer player who plays for Brentford Football Club in the English Premier League, was banned from soccer for eight months and fined $62,500 after being found guilty of 232 breaches of the Football Association spendin…
REVERSE PSYCHOLOGY | 13 LESSONS on how to use REJECTION to your favor | Marcus Aurelius STOICISM
Have you ever had a door slammed shut in your face only to realize it was the best thing that could have happened to you? Today, we’re going to explore the skill of overcoming rejection head-on, drawing inspiration from the teachings of the stoic philosop…
Playing Sci-Fact or Sci-Fiction | StarTalk
Now we’re going to play a game called SFA or SCI fiction, and you’re going to identify whether you think it is SFA or a sci fiction or maybe you don’t know if I don’t know either. I won’t claim to know. That sounds good. The days were shorter millions of…
Slow Motion Ice Bucket Challenge (Dog, Cat, Chicken, Kid) - Smarter Every Day
Hey, it’s me Destin and welcome back to Smarter Every Day. So I was challenged by Grant Thompson to do the Ice Bucket Challenge and I want to do a video that’s smart and teaches you something, that’s fun to watch and something that actually ends up giving…
This is the World’s Most Expensive Spice | National Geographic
[Music] [Music] This is a farm in Horizonte’s in north-east of Iran. Saffron is known as the most valuable plant in the world and has been growing in Iran for thousands of years. Saffron stems from Iran’s history, knowledge, and experience. Aboard, saffro…
Quantitative information in texts | Reading | Khan Academy
Hello readers! Today we’re going to talk about quantitative information in texts. But I want to start with a question: What’s the best way to describe the way a horse looks as it runs? What’s the most efficient way? I guess I could just use words, right?…