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32 Cards in this Set
- Front
- Back
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Population to Sample is? |
Probability |
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What is probability? |
# of outcomes specified as variable / total # of outcomes |
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What is the notation used for probability? |
p (variable) |
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What are the 2 random sampling conditions? Why and how are they met? |
Random sample: equal chance of being selected (no bias in selection process) Independent random sample: random sample and the probability of being selected stays constant (Sampling with replacement) |
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For a unit normal table, what is the tail and what is the body of a distribution? |
Tail: smaller portion Body: larger portion |
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How do you find probabilities for an X value? |
Convert X value into a z-score and find the % using the unit normal table |
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What is a DSM? What are it's characteristics? (3) |
Distribution of sampling means: a collection of all the possible samples collected from a population - should pile up around mean and should make a normal distribution (if the sample size is large enough) |
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How big does a sample size need to be to have a DSM form a normal distribution? What if the original distribution isn't normal? |
n=30 Doesn't matter if it is or isn't. |
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What is the Central Limit Theorem? |
Population- u and o Sample- u and o÷ √n |
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What is the Standard Error of M? |
Om= o÷√n - the expected distance from sample mean and population mean |
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What is the law of large numbers? |
States that the larger the n value, the standard error decreases |
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What happens to the standard error if n=1? |
Standard error= standard deviation |
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What is the expected value of M? |
DSM= population mean |
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What is one basic assumption of Hypothesis testing situations? |
If the treatment has any effect, it's simply adding/subtracting constant from each score |
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What are the 4 steps to hypothesis tests? |
1. State 2 of the hypotheses 2. Set the criteria 3. Collect data 4. Make a decision |
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What are the 2 types of hypotheses? |
Null Alternative |
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How do you compute sample stats? (Step 3 of Hypothesis Testing) |
z= M-u/Om |
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What are the 2 decisions you can make? |
Reject null (there's an effect) Fail to reject null (there's no effect) |
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What is a type 1 error? How do you measure it's probability? |
Reject null when you there is no effect - alpha level |
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What is a type 2 error? How do you measure it's probability? |
Fail to reject the null when there was an effect - beta level |
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True or False: the smaller the alpha level the better |
False |
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If p< 0.05...? |
Reject null |
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What factors influence hypothesis testing? |
When standard deviation/error is high, the z scores are closer to 0 |
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What are the assumptions by Hypothesis Testing? (2) |
1. Random sampling 2. Standard deviation doesn't change after treatment |
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What is a directional hypothesis test? |
One tailed test, increase or decrease effects ONLY |
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What makes a treatment effect large enough to be significant? |
The size of the sample (if it's big enough) |
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How do you measure effect size? What are the results? |
Cohen's d= M(treatment) - u(no treatment)/ o - 0.2= small - 0.5= medium - 0.8= large |
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What is a power of a statistical method? |
The probability of correctly rejecting a null and identify a treatment effect |
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As effect size increases, power....? |
Increases |
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As sample size decreases, power...? |
Decreases |
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What happens to the z-score when the SD increases? |
Decreases (closer to 0) |
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How is variance effected by the n value? |
Higher n value= lower variance |
