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(Hypothesis Testing (4 Step process (4) Make a decision (B) Reject Ho if…

- - - - B) Reject Ho if the obtained z score is in the critical region because it's very unlikely that these data would be obtained if Ho were true
      - A) Fail to reject Ho if Z score is not in the critical region because the data are not significantly different from the null hypothesis
  - - - has +/- sign
  - - - increase alpha
      - conduct a one tailed test
      - increase the effect size (cohen D)
      - decrease random error
      - increase sample size (n of 30 or more)
- - - - Requires that each individual in the population has an equal chance of being selected = Simple random sample
      - IF more than 1 individual is being selected, the probabilities must stay constant from 1 selection to the next = Independent random
      - Sampling with replacement
        
        Sampling technique that returns current selection to the population before next selection is made
        
        Required part of random sampling
  - - - Symmetrical w/ a single mode in the middle
      - Frequency tapers off as you move farther from middle in either direction
      - Use the unit normal table to identify proportions/probabilities for specific Z-score values and Z score locations
        
        What's in Unit Normal Table?
        
        Column A of table - list Z scores
        
        Column B lists proportion in the body
        
        Column C lists proportion in tail
        
        Column D lists proportion between the mean and the Z-score
    - - shows the probability associated with each value of X from X=0 to X=n
        
        can be used to answer probability questions
        
        binomial distribution tend to be normal
- - - - 1) describes distribution of sample means for any population nor matter what shape, mean or standard deviation (shape, central tendency, variability)
      - 2) distribution of sample means "approaches" a normal distribution very rapidly ie. if sample size n=30 the distribution is almost perfectly normal
      - The Mean of the Distribution of Sample Means
        
        the mean of the distribution of sample means always is identical to the population mean
        
        this mean value = Expected value of M
      - Standard Error of M
        
        purposes
        
        1) describes distribution of sample means - provides a measure of how much difference ie expected from one sample to another. when SD error is small, all the sample means are close together and have similar values.
        
        2) measures how well an individual sample mean represent the entire distribution. it provides a measure of how much distance is reasonable to expect between a sample mean and the overall mean
        
        Magnitude determined by 2 factors
        
        1) size of sample - as sample size increased, less error between sample mean and population mean
        
        2) standard deviation of the population from which the sample is selected