Don’t argue! Refer to Exercise 2. For Yvonne’s survey, 96...

Name: Problem 12, Chapter 9: The Practice of Statistics for AP
Uploaded: 2020-04-11T19:12:23-08:00
Duration: 2 min 42 s
Channel: Andrew Shoemaker
Description: Don’t argue! Refer to Exercise 2. For Yvonne’s survey, 96 students in the sample said they rarely or never argue with friends. A significance test yields a P-value of 0.0291. (a) Interpret this result in context. (b) Do the data provide convincing evidence against the null hypothesis? Explain.

Don’t argue! Refer to Exercise 2. For Yvonne’s survey, 96 students in the sample said they rarely or never argue with friends. A significance test yields a P-value of 0.0291. (a) Interpret this result in context. (b) Do the data provide convincing evidence against the null hypothesis? Explain.

Don’t argue! Refer to Exercise 2. For Yvonne’s survey, 96 students in the sample said they rarely or never argue with friends. A significance test yields a P-value of 0.0291.
(a) Interpret this result in context.
(b) Do the data provide convincing evidence against the null hypothesis? Explain.

Key Concepts

Hypothesis Testing

Hypothesis testing is an inferential statistical method used to make decisions or inferences about population parameters based on sample data. It involves formulating a null hypothesis that represents a baseline or status quo, and an alternative hypothesis that reflects what the researcher aims to support.

Null Hypothesis

The null hypothesis is a statement asserting that there is no effect, no difference, or no association in the population. In the context of a survey or experiment, it posits that any observed differences or patterns in the sample are due to random chance.

Alternative Hypothesis

The alternative hypothesis is what researchers propose as an alternative to the null hypothesis. It suggests that there is a real effect, difference, or association in the population, and the data provide evidence against the null hypothesis if this alternative is supported.

P-value

The P-value is the probability of observing a test statistic at least as extreme as the one obtained from the sample data, under the assumption that the null hypothesis is true. A smaller P-value indicates stronger evidence against the null hypothesis, implying that the observed result is unlikely to have occurred by chance alone.

Significance Level

The significance level, often denoted by ?, is a threshold chosen by the researcher to determine when to reject the null hypothesis. If the P-value is less than this predetermined significance level, the results are considered statistically significant, providing convincing evidence against the null hypothesis.

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