Two Sample Inference for Means
... Independent sample observations. Random sample. Unknown variance. Two distributions have different variance, as per F test. ...
... Independent sample observations. Random sample. Unknown variance. Two distributions have different variance, as per F test. ...
Math 230 Sample Final Exam
... Answer: The sample size n = 10 is small (n < 30) and thus a t distribution is needed to develop the desired twosided CI for the Susanne’s elastic population mean. For this one-sample population case, the degrees of freedom (df) = n – 1 = 9. Using our beloved t-table, we see that the appropriate t-va ...
... Answer: The sample size n = 10 is small (n < 30) and thus a t distribution is needed to develop the desired twosided CI for the Susanne’s elastic population mean. For this one-sample population case, the degrees of freedom (df) = n – 1 = 9. Using our beloved t-table, we see that the appropriate t-va ...
H 0
... standard deviation, S • This introduces extra uncertainty, since S is variable from sample to sample => Use the t distribution instead of the normal distribution Assumptions – Population standard deviation is unknown – Population is normally distributed – If population is not normal, use large sam ...
... standard deviation, S • This introduces extra uncertainty, since S is variable from sample to sample => Use the t distribution instead of the normal distribution Assumptions – Population standard deviation is unknown – Population is normally distributed – If population is not normal, use large sam ...
Reject H 0
... We can never know if the test provided the correct answer, we can only control the probability of making a certain type of error. Level of significance – the probability of making a Type I error when the null hypothesis is true as an equality. ...
... We can never know if the test provided the correct answer, we can only control the probability of making a certain type of error. Level of significance – the probability of making a Type I error when the null hypothesis is true as an equality. ...
