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| describe the characteristics of a set of numbers |
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| methods for making void statements about an entire population based on a sample |
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| if a population has a mean and a standard deviation than the distribution of sample means drawn from this population approaches a normal distribution as n increases with a mean of u/M and a standard deviation of o/{n |
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| standard error of the mean |
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Definition
| the standard deviation of the sampling distribution o/{n |
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| the probability that a result is due to the sampling error |
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| a range of acceptable values to determine the 95% confidence interval you calculate the boundaries M + or - 1.96 * o/{n |
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| 95% interval that it is likely to happen |
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Definition
| it is in the 5% probability that it would be unlikely to happen |
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| sample size effect Smaller sample = |
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Definition
| the bigger the confidence interval |
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| sample size effect larger the sample = |
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Definition
| smaller the confidence interval |
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| Four types of single factor designs |
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Definition
1.Between Subjects- Independant group (each group only participates in one group) 2.Matching Groups (matched on relevant variable) 3.Non-Equivalent Group (people are assign based on some characterisitic.) 4.Within Subject-Repeated measures (each group participates in one condition. |
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1.Placebo 2.Waiting 1st Control Group 3.Yoked control group |
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| Why are z-scores non reliable? |
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| we usually do not know the standard deviation of the population |
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Definition
for IND..df=(n-1)+(n2-1) DEP df=(n-1) |
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Definition
Reject the null hypothesis if step 3 is higher than step 2 or step 3 is negative
(subject) is significantly higher than (Agroup) (m=#) than (Bgroup) (m=#), t=(df)=(tc), p<.05 |
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| Assumptions underlying t-tests IND |
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Definition
| IND refers to scores within each group/sample |
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| Assumptions underlying t tests NORMALLY distributed difference scores |
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Definition
| difference scores should be normally distributed in the population |
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