Test 2 Flashcards
What is a sampling distribution? Why is the concept of the sampling distribution important?
Theoretical distribution that consists of the means scores of all possible samples of a given size from population. Its important because it gives us all possible sample results.
Describe in words the null and alternative hypotheses and give the symbol for each.
null hypothesis is our results are due to chance. Nothing that really effects the results at all.
Alternative hypothesis is our results are due to something other than chance.
Identify and define the two types of potential errors when rejecting or retaining the null hypothesis.
Type 1: false alarm, when you reject null hypothesis when you should have accepted it. You say there is an effect when there really isn’t.
Type II: A miss, when you fail to reject your null hypothesis when you should have. When you say there is no effect but there really is.
Explain the difference between directional and nondirectional hypotheses.
directional: is one tailed and very specific of where our results are going to fall.
Non directional: two tailed, the 5 percent splits both sides and prediction isn’t at specific.
What are the assumptions underlying the use of t-distributions?
- Sampling distribution is normally distributed and if this is violated the results really aren’t as accurate.
- Homogeneity of variance- this is where the two populations where we are comparing have similar variance.
- roughly equal variances.
What is the difference between independent samples designs and repeated measures designs?
The independent sample is where you have a control group and a additive/treatment group and its two different groups with different people. Repeated measures is where you have the same person being treated and is in the control group and treatment group.
What are the degrees of freedom in the paired-samples t-test? How does this differ from the degrees of freedom in the independent samples t-test? How do the differences in df influence the critical t-value?
paired samples: n-1-: a normal influence to find the critical t-value.
Independent sample t test n1+n2-2. :can sometimes not be as accurate when it comes to the critical t-value.
Higher for independent which makes critical value lower
What is the advantage of a repeated measures design over an independent samples design?
Repeated measures account for individual differences and independent groups do not.
What is the relationship between the level of significance and a type 1 error? and a type 2 error?
The alpha level= chance of making type 1 error.
As 0.5 goes down to 0.1 it decrease type 1 but increase type 2.
the alpha level = chance of making type 1 error.
What is the relationship between the size of N and the standard error of the mean?
As the sample size increases your standard error decreases.
What does the standard error of the mean indicate?
the standard error of the mean indicates the estimation of the population mean. Also, it can refer to an estimate of the standard deviation; computed from the sample data being analyzed at the time.
What is the standard error of the difference between means?
When each point refers to each sample mean. You take the two means and subtract them.
