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AMU MATH 120 Week 7 Hypothesis Testing with One Sample

Master statistical hypothesis testing for means and proportions

Week 7 Hypothesis Testing

Week 7 introduces hypothesis testing—the process of using sample data to make decisions about population parameters. You'll learn to state null and alternative hypotheses, calculate test statistics, find p-values, make decisions using significance levels, and interpret results in context. The week covers hypothesis tests for population means (σ known or unknown) and population proportions, teaching you to distinguish between Type I and Type II errors.

Common Week 7 Struggles

Students often confuse null and alternative hypotheses, write them incorrectly, or misinterpret p-values. Another challenge is determining whether to use one-tailed or two-tailed tests. The decision rule (reject or fail to reject) also causes confusion—many students incorrectly say 'accept the null hypothesis.' Our materials include hypothesis writing templates, p-value interpretation guides, and decision flowcharts for one-tailed vs two-tailed tests.

Week 7 Support Resources

You receive complete MyStatLab Homework 7 solutions, hypothesis testing formula sheets, p-value calculation guides, test statistic examples for every scenario, and forum posts connecting hypothesis testing to quality control, medical research, and business decisions. We provide practice problems that build intuition for when results are statistically significant versus practically significant.

Frequently Asked Questions

❓How do I write null and alternative hypotheses correctly?

The null hypothesis (H₀) always contains equality (=, ≤, or ≥). The alternative hypothesis (Hₐ) contains the claim being tested (<, >, or ≠). For example, to test if mean is greater than 50: H₀: μ ≤ 50, Hₐ: μ > 50. The alternative determines if you use a one-tailed or two-tailed test.

❓What does the p-value actually mean?

The p-value is the probability of getting your sample result (or more extreme) if the null hypothesis is true. Small p-values (typically < 0.05) suggest your sample result is unlikely under H₀, so you reject H₀. Large p-values suggest your result is consistent with H₀, so you fail to reject H₀. Never say 'accept H₀'—only 'fail to reject H₀.'

❓When do I use a one-tailed vs two-tailed test?

Use a one-tailed test when the alternative hypothesis uses < or > (testing if parameter is less than or greater than a value). Use a two-tailed test when the alternative uses ≠ (testing if parameter is different from a value). The alternative hypothesis determines the test type—look for directional words like 'more than' or 'less than' for one-tailed.

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