## Why are random sampling distributions used in null hypothesis significance testing?

### statistics

##### Description

NORTHERN CARIBBEAN UNIVERSITY

A. Concepts

1.      Using appropriate diagrams, illustrate the development and meaning of random sampling distribution of means.

2.      Why are random sampling distributions used in null hypothesis significance testing?

3.      What is the meaning of the following terms/phrases: a. statistical significance b. type 1 eyror

c. relative frequency d. percentile rank e. p is less than 0.001

4.      Suppose a researcher rejects the null hypothesis, does this mean that the alternative hypothesis is true and it is therefore confirmed?

5.      Explain the following: (a)...John's percentile rank is 75 (b)..the relative frequency yes/affirmative votes is 0.40. (c) ..the odds of displaying autism in this population is 0.10.

6.      A. What % of scores would be higher than Man/s if her percentile rank is 65? B. What is likelihood that Shane would obtain a score above the 80th percentile? Justify your answers by using relevant diagrams and state your assumptions.

7.      What is the likelihood of obtaining each of the following scores given the corresponding mean and standard deviation of the distribution: a. score= 25, mean=12, sd=2.5; score=36, mean=30,sd=5. Show how you arrive at your answers.

8.      Explain the following: a. Analyses indicate that the relation between pain tolerance for men (b= -0.02) and for women (b=O.31). b. response speed at maximal stimulus strength

9.      Explain the following: "...with regard to perceived confidence, workshop attendees felt more confident (t(89)=5.28,p<O.001)..."

10.  What are similarities and differences between odds ratio and regression coefficients?

B. Computer Application:

1.  Develop a Variable and Data View.  Submit the files.

2.  Conduct (a) an independent samples T-Test,  (b) a regression analysis using MCAT Science scores as the outcome (dependent) and ACT composite as the predictor (independent) and (c) a correlation analysis.

Submit the outputs.

3.  Examine the 4 assumptions of regression and those for using the T- Test.  Submit graphical outputs and your interpretations thereof.

4.  Write  a report.  ( Include: Hypotheses, levels of significance, conclusion).