Hypothesis Testing

Hypothesis testing is a statistical approach that allows us to make educated guesses or conclusions about a larger group by examining a smaller sample. This process includes establishing a null and an alternative hypothesis, selecting a level of significance, determining the test statistic, and finally deciding whether to uphold or dismiss the null hypothesis.

Setting the Alternative Hypothesis

A company claims that the mean number of sick days taken by its employees is less than 3 days. A random sample of 36 employees is selected, and it is found that they have taken an average of 2.8 sick days with a standard deviation of 0.5. Is there sufficient evidence to support the company's claim at a 0.05 level of significance?

Setting the Null Hypothesis

A company claims that their new energy drink increases the average energy level of an individual by 1.5 points on a scale of 10. To test this claim, a random sample of 36 individuals are selected and given the energy drink. The average increase in energy level for these individuals was found to be 1.7 with a standard deviation of 0.5. Can we reject the company's claim at a 5% level of significance?

Determining if Left, Right, or Two Tailed Test Given the Null Hypothesis

A company claims that its new diet pill reduces the weight by more than 5 pounds on average in a week. A sample of 30 people are tested and the mean weight loss is found to be 5.3 pounds with a standard deviation of 1.2 pounds. Using a significance level of 0.05, is there sufficient evidence to support the company's claim? The null hypothesis is that the mean weight loss is 5 pounds.

Determining if Left, Right, or Two Tailed Test Given the Alternative Hypothesis

A company claims that their average customer satisfaction score is 85. A sample of 30 customers is taken, and their average score is 82 with a standard deviation of 3. The alternative hypothesis is that the average customer satisfaction score is not 85. What type of test should be used?