Hypothesis Testing
Describe the difference between the null hypothesis and the alternative hypothesis
Null hypothesis is what you area actually testing; it is the hypothesis which states that there are no differences between the groups you are testing.
Alternative hypothesis states the difference you are interested in between groups
T tests compare how many groups?
2
What are the three components of a Confidence Interval calculation
Point estimate, Z critical, and standard error/deviation
An ANOVA compares how many groups?
3+
A group of researchers hypothesize that 10mg of an antidepressant will have less side effects than 20mg. Write an inequality to describe the null and alternative hypotheses
Where Mu1 = 10mg and Mu2 = 20mg:
H0: Mu1 = Mu2
H1: Mu1 < Mu2
If the T-statistic is beyond the T critical, what do we do?
Reject the null hypothesis
What is the difference between the calculation for a CI for proportion and mean?
What does the F-statistic represent?
The ratio of the average variability within groups, to the average variability within the groups.
A group of researchers hypothesize that 10mg of an antidepressant will have a different amount of side effects than 20mg. Write an inequality to describe the null and alternative hypotheses
Where Mu1 = 10mg and Mu2 = 20mg:
H0: Mu1 = Mu2
H1: Mu1 ≠ Mu2
What are the three kinds of T-tests? Describe each.
Independent samples; Dependent samples; and One-sample
What Z-critical values correspond to 90%, 95%, and 99% confidence levels?
1.645, 1.96, and 2.575, respectively
Why would you conduct a single ANOVA instead of multiple t-tests to compare more than 2 groups?
When you conduct a T-Test, there is a chance that you will run into a Type 1 error and the chance of running into this error compounds with each T-test you run. So, you run a single ANOVA to reduce this chance.
A group of researchers hypothesize that 10mg of an antidepressant will have more side effects than 20mg. Write an inequality to describe the null and alternative hypotheses
Where Mu1 = 10mg and Mu2 = 20mg:
H0: Mu1 = Mu2
H1: Mu1 > Mu2
What is the Formula for the T statistic in a One sample T test?
Sample mean (X-bar) minus the population mean (Mu) over the sample standard deviation (S) over the square root of the sample size (n).
Interpret a 99% confidence interval with a lower limit of 6.95 feet and an upper limit of 8.21 feet.
We are 99% confident the true population mean of X is between 6.95 feet and 8.21 feet.
If the F-statistic is lower than the F-critical, what does this mean for the null hypothesis? Why?
We DO NOT reject the null hypothesis as there is not sufficient evidence that the group means are different enough.
True or False; All ANOVA hypothesis tests can be written as an inequality
False; The alternative hypothesis cannot be written as an inequality as there are too many variation.
BONUS: Interpret a P-value of .001 in relation to the Null and Alternative hypothesis
There is a less than .01% chance of these results occurring if the null hypothesis were true.
The reason this is interesting is because even if you reject the null hypothesis, it may be the case your results occurred by chance.