I.     Sampling Distributions

A. All the values that the statistic can take

B. The probability of getting each value under the assumption that it resulted from chance alone

C.Null-Hypothesis Population

1.               

2.               

3.              It is used to

4.              2 Approaches

a)              Empirical Sampling -

b)             A Priori -

II.  The Normal Deviate (z) Test

A. Sampling Distribution of the Mean

1.               

2.               

3.              4 characteristics

a)              Is a distribution of scores where

(1)           
(2)           
(3)           

b)             Has a mean =

c)              Has a standard deviation

d)             Is normally shaped, depending on

(1)           
(2)           
(3)           

B. Example:

1.              Population mean = 75, sd = 16, N = 100

2.              Determine sampling distribution of the mean

a)              Mean =

b)             Standard Error of Estimate =

(1)          = 16/ square root of 100
(2)          = 16/10 therefore
(3)          = 1.6

c)              Transform to Z obt

(1)          Z obt =
(2)          = 72 - 75/1.6
(3)           = -1.88

d)             Determine Probability, From to Table A, column C

(1)          = 0.0301
(2)          Compare to Alpha  = .05
(3)          .0301 < .05, therefore reject the null hypothesis - accept the alternate hypothesis, independent var affects dependent var

C.Preferred Solution - Using Zobt and the Critical Region for Rejection of Ho

1.              Critical Region for rejection of the null hypothesis -

2.              Critical Value of a statistic -

3.              Determine Zcrit by using table A in reverse

a)              1 tail - Zcrit = 1.645, since left side of dist, actually -1.645

b)             2 tails - Zcrit = +/- 1.96

c)              If absolute value of Zobt >= absolute value of Zcrit, reject null hyp

d)             So for our example, reject 1 tail, fail to reject 2 tail

III.          When is Z test Appropriate

A.  

B.  

C.The sampling distribution of the mean should be normally distribution - true if

1.               

2.               

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