chapter 9 words
Significance level:
The risk associated with not being
100% positive that what occurred in the experiment is a result of what is being tested.
Computing the Z-Test Statistic
z= mean of the sample - mean of the population divided by standard error of the mean
Statistical significance
The degree of risk you are
willing to take that you will reject a null hypothesis
when it is actually true.
interpret z = 2.38, p < .05
– z represents the test statistic used.
– 2.38 is the obtained value (from the formula).
– p < .05 indicates that the probability that the results occurred randomly are less than 5% and are
therefore statistically significant
Type I Errors
-The probability of rejecting a null hypothesis when it is
true.
- Conventional levels are set between .01 and .05.
- Usually represented in a report as p < .05.
Computing the Standard Error of the
Mean
sem=the standard deviation for the population divided by the size of the sample
How Inference Works
-Step 1: Select representative samples.
-Step 2: Collect the relevant data.
-Step 3: Reach a conclusion as to whether the
difference between the scores is the result of chance.
-Step 4: Reach a conclusion that applies to the whole population based on the finding within the samples.
A small effect size ranges from
0.0 to .20.
How to Select Which Test to Use
• On the next slide, you will see a cheat sheet on how to
select which test to use.
• Start by answering the questions at the top of the
flowchart.
• Proceed down the chart by answering each of the
questions until you get to the end of the chart.
A large effect size is any value
above .50.