University:
York University
Course:
AP/ADMS 2320 | Business Statistics
Academic year:

2022
Views:

392

Pages:

2
Author:

Niklas

One Sample Hypothesis Testing lecture S Ho = null hypothesis: states nothing will change H1 = alternate hypothesis: states a change aim is to see if we can reject null hypothesis if the critical value is too low, there's danger of false positive, but if too high, there's danger of false negative Lo type I error = we rejected Ho when Ho was true Lo type II error = we didn't reject Ho, when Ho was false test statistic must be higher than CV to reject null hypothesis CV is predetermined level of significance (α) = smaller = more evidence needed to reject Ho Lo Common αs = 10%, 5%, 1% Lo p-value is αs that can reject Ho example: Example 9. Referring to the scenario in examples 7 and 8, suppose that in a sample of n = 30 days the average number of sales was x̄ = 2150. The standard deviation is known to be σ = 300. Would you reject the null hypothesis H₀: μ = 2000 in favour of the alternative hypothesis H₁: μ > 2100, at a significance level α = 5%? x̄ = 2150, σ = 300, n = 30 H₀: μ = 2000 vs H₁: μ > 2100 α = 5% = 0.