XodoX said:Homework Statement
Consider N(μ, σ2=40) distribution. To test H0:=32 against H1:μ>32, we reject H0if the sample mean [itex]\overline{X}[/itex]≥c. Find the sample size n and the constant c such that OC(μ=32)=0.90 AND OC(μ=35)=0.15.
Homework Equations
What I don't know
The Attempt at a Solution
Can't figure out how to do this one.
Ray Vickson said:Show your work. Tell us why you cannot just use the material from the textbook or the course notes to get started with this problem.
RGV
A hypothesis is a proposed explanation for a phenomenon or observation. It is a tentative statement that can be tested and supported or rejected through scientific research and experimentation.
The purpose of tests of hypotheses in statistics is to determine whether there is enough evidence to support a specific hypothesis. These tests involve collecting and analyzing data to determine if the results are statistically significant, meaning that they are unlikely to have occurred by chance.
In a one-tailed test of hypothesis, the alternative hypothesis is directional and predicts the outcome in a specific direction. In a two-tailed test of hypothesis, the alternative hypothesis is non-directional and predicts that the outcome will be different from the null hypothesis, but does not specify a direction.
A p-value is the probability of obtaining results at least as extreme as the observed results of a statistical test, assuming that the null hypothesis is true. It is used to determine the significance of the results and is compared to a predetermined significance level to determine if the results are statistically significant.
The results of a test of hypothesis can be interpreted by comparing the p-value to the significance level. If the p-value is less than or equal to the significance level, the results are considered statistically significant and the null hypothesis can be rejected. If the p-value is greater than the significance level, the results are not statistically significant and the null hypothesis cannot be rejected. It is important to also consider the practical significance of the results in addition to the statistical significance.