This statlet tests hypotheses about the mean and standard deviation of a normal distribution. The tabs are:
To use this statlet, enter the following information about your data:
Data label - a name to be displayed on the output.
Sample size - the number of observations in the sample.
Sample mean - the mean of the sample.
Sample standard deviation - the standard deviation of the sample.
This tab shows the result of a hypothesis test concerning the population mean:
It shows:
Summary statistics.
A confidence interval for the mean.
The result of a t-test run to test a hypothesis about the population mean.
Use the Options button to specify the hypotheses to be tested. If the P-value is less than the alpha risk which you specify, you should reject the null hypothesis at the corresponding significance level.
Enter:
Null hypothesis - the value of the mean specified by the null hypothesis.
Alt. Hypothesis - select a two-sided test (~=) or a one-sided test.
Alpha - the probability of a Type I error, which is a situation where a true null hypothesis is incorrectly rejected. Typical values for alpha are 10%, 5%, and 1%. The confidence interval is also affected by this setting and uses a confidence level equal to (100-alpha)%.
This tab shows the power curve for the t test:
The power curve shows the probability of rejecting the null hypothesis as a function of the true population mean.
Same as previous tab.
This tab shows the result of a hypothesis test concerning the population standard deviation
It shows:
Summary statistics.
A confidence interval for the standard deviation.
The result of a chi-squared test run to test a hypothesis about the population sigma.
Use the Options button to specify the hypotheses to be tested. If the P-value is less than the alpha risk which you specify, you should reject the null hypothesis at the corresponding significance level.
Enter:
Null hypothesis - the value of the standard deviation specified by the null hypothesis.
Alt. Hypothesis - select a two-sided test (~=) or a one-sided test.
Alpha - the probability of a Type I error, which is a situation where a true null hypothesis is incorrectly rejected. Typical values for alpha are 10%, 5%, and 1%. The confidence interval is also affected by this setting and uses a confidence level equal to (100-alpha)%.
This tab shows the power curve for the chi-squared test:
The power curve shows the probability of rejecting the null hypothesis as a function of the true population sigma.
Same as previous tab.