PSYC2525 Psychology

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PSYC2525 Psychology

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PSYC2525 Psychology

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Course Code: PSYC2525
University: Louisiana State University

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Country: United States

Question:

Write the null and alternative hypotheses for the following (use symbols):

Two tailed Z test

H0:
H1:

One Tailed Z Test

H0:
H1:

Area under the normal curve

Area between 2 sd above and the mean (z scores of 0 and 2.0)
Area below z score of 1
Z score below which 95% of all values fall

Fill in the following table about Type I and Type II errors

Decision you

make

Fail to reject the null hypothesis (Accept)

Reject the null hypothesis

True nature of the null hypothesis

The null hypothesis is really true

The null hypothesis is really false

What is power and what is the formula for power

Compute the z scores for the following scores from a sample with a standard deviation of 10 and a mean of 50:

78
92
38
44

Compute the one sample Z-test for the following problems.A test is conducted for H0: μ = 40, with σ = 5.  A sample size of 100 is selected = 42.2 What is the null and alternative hypothesis for a 2-tailed test of significance?

Compute the SEM for this problem.Compute the one Sample Z-test for this problem.

Answer:

Standard Normal Table Used to Answer 2a, 2b, and 2c (Thomopoulos, Nick, 2018, p. 45-55).

Required area = = 0.47725
Required area = =  5 + 0.341345 = 0.841345 = 0.84
, so required Z-score = 1.645 below which 95% of the values will be positioned.

Decision you
make

Fail to reject the null hypothesis (Accept)

Reject the null hypothesis

True nature of the null hypothesis

The null hypothesis is really true

Correct Conclusion

Type –I error

The null hypothesis is really false

Type –II error

Correct Conclusion

ANS: Power in testing of hypothesis is the technique of selecting the correct choice. Hence, it is the probability that is associated with rejection of a false null hypothesis. Power of a test is calculated as (1 – probability of Type –II error) or simply , where is the probability of accepting or failing to reject a false null hypothesis (Park & Hun Myoung, 2015).
ANS: The relation between normal (X) and standard normal variable is known to be as , where is the mean and is the standard deviation of X variable.

=>
X = 92 =>
X = 38 => Z =
X = 44 =>

ANS:

For two tailed test of significance,

Null Hypothesis: H0: ( ) and
Alternate Hypothesis: HA: ( )
The considerations are taken accordingly at specified level of significance (D’Agostino, RalphB, 2017).

SEM (Standard Error of the Mean) =
For one tailed test of significance,

Null Hypothesis: ( ) and
Alternate Hypothesis: ( ) at given level of significance (Sullivan & Michael, 2015)
References
D’Agostino, RalphB. Goodness-of-fit-techniques. Routledge, 2017.
Park, Hun Myoung. “Hypothesis testing and statistical power of a test.” (2015).
Sullivan III, Michael. Fundamentals of statistics. Pearson, 2015.
Thomopoulos, Nick T. “Standard Normal.” Probability Distributions. Springer, Cham, 2018. 45-55.

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