From the course: Statistics Foundations 3: Using Data Sets
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Significance test for proportions
From the course: Statistics Foundations 3: Using Data Sets
Significance test for proportions
- Let's imagine we're working for a candidate's campaign team. We find that in a random sample of 500 eligible voters, 54% of those polled said they plan on voting for our candidate. Our candidate needs over 50% of the vote to win the election. So the poll looks pretty good, but in an effort to better understand the polling results, we decide to use hypothesis testing. Let's take a look. Step one, we need to develop the hypotheses. H0, our null hypothesis, indicates that the candidate has not won and will not win the election. So p is less than or equal to 0.50. In other words, the hypothesis states that the candidate would get 50% or less of the votes, not enough votes to win the election. H sub a, our alternative hypothesis, indicates the candidate wins. Thus, our alternative hypothesis is p is greater than 0.50. The candidate will get a majority of the vote and win. Step two, our significance level for this test will…
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