1. Is there statistically significant evidence for the alternative hypothesis? N

Question

1. Is there statistically significant evidence for the alternative hypothesis? Null hypothesis: Population mean = 155 Alternative hypothesis: Population mean>155 n: 50 Sample Mean: 157.8 Standard Erro 2.093 df t statistic:1357 P-value: 49 0.09056 2. Suppose you somehow find out that the actual mean height for the entire database population is 160 cm. Looking back at your test from question 1, was the result of your test a correct decision, a Type I error, or a Type Il error. Explain (for example, did you reject a true null, fail to reject a false null, reject a false null, or fail to reject a true null). 3. Suppose you somehow find out that the actual mean height for the entire database population is 155 cm. Looking back at your test from question 1, was the result of your test a correct decision, a Type I error, or a Type Il error. Explain

Explanation / Answer

1.In principle, a statistically significant result (usually a difference) is a result that's not attributed to chance. More technically, it means that if the Null Hypothesis is true (which means there really is no difference), there's a low probability of getting a result that large or larger.

In other words

If your p-value is less than or equal to the set significance level, the data is considered statistically significant. As a general rule, the significance level (or alpha) is commonly set to 0.05, meaning that the probability of observing the differences seen in your data by chance is just 5%.

Here we see that pvalue>alpha=0.05 hence it is not statistically significant.

Related Questions

Navigate

• Browse (All)
• Browse 1
• Subjects

---

---

Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.