Main Task: Submit the Following  1.  Calculate the sample size needed given these factors: · one-tailed t-test with two independent groups of equal size · small effect size (see Piasta, S.B., & Justice, L.M., 2010) · alpha =.05 · beta = .2 · Assume that the result is a sample size beyond what you can obtain. Use the compromise function to compute alpha and beta for a sample half the size. Indicate the resulting alpha and beta. Present an argument that your study is worth doing with the smaller sample. 2.  · Calculate the sample size needed given these factors: · ANOVA (fixed effects, omnibus, one-way) · small effect size · alpha =.05 · beta = .2 · 3 groups · Assume that the result is a sample size beyond what you can obtain. Use the compromise function to compute alpha and beta for a sample approximately half the size. Give your rationale for your selected beta/alpha ratio. Indicate the resulting alpha and beta. Give an argument that your study is worth doing with the smaller sample. 3. In a few sentences, describe two designs that can address your research question. The designs must involve two different statistical analyses. For each design, specify and justify each of the four factors and calculate the estimated sample size youll need. Give reasons for any parameters you need to specify for G*Power. Include peer-reviewed journal articles as needed to support your responses to Part I. Support your paper with a minimum of 5 resources. In addition to these specified resources, other appropriate scholarly resources, including older articles, may be included. Length: 5 pages not including title and reference pages ExamB/ExamB.php <?php // get user file $filename = $_REQUEST['filepath'] ; $validate = true ; $x = array(); $y = array(); // var to get Point variable $X_avg = $X_sum = 0 ; $Y_avg = $Y_sum = 0 ; if (!file_exists($filename)){ echo "Please correct file path." ; } else // >>>>>>>>>>>>>>>>>> HERER <<<<<<<<<<<<<<<<<<<< // { // load code file $Points = file_get_contents($filename) ; // get code lines $Points_lines = explode("\n", $Points); // validate empty line foreach ( $Points_lines as $line) { if(strlen($line) == 0 ) { $validate = false ; $validate_message = "Empty Line" ; } } // validate pairs & Numbers if($validate) foreach ( $Points_lines as $line) { $Pairs = explode(",", $line); if(strlen($Pairs[0]) == 0 || strlen($Pairs[1]) == 0 ) { $validate = false ; $validate_message = "Pairs Mismatching " ; break; } else { if(is_numeric($Pairs[0]) && is_numeric($Pairs[1]) ) { $validate = true ; } else { $validate = false ; $validate_message = "Only numeric accepted" ; break ; } } } // validate >= 0 if($validate) foreach ( $Points_lines as $line) { $Pairs = explode(",", $line); if(($Pairs[0] > 0 ) && ($Pairs[1] ...

1. Main Task: Submit the Following
1.
Calculate the sample size needed given these factors:
· one-tailed t-test with two independent groups of equal size
· small effect size (see Piasta, S.B., & Justice, L.M., 2010)
· alpha =.05
· beta = .2
· Assume that the result is a sample size beyond what you can
obtain. Use the compromise function to compute alpha and beta
for a sample half the size. Indicate the resulting alpha and beta.
Present an argument that your study is worth doing with the
smaller sample.
2.
· Calculate the sample size needed given these factors:
· ANOVA (fixed effects, omnibus, one-way)
· small effect size
· alpha =.05
· beta = .2
· 3 groups
· Assume that the result is a sample size beyond what you can

2. obtain. Use the compromise function to compute alpha and beta
for a sample approximately half the size. Give your rationale for
your selected beta/alpha ratio. Indicate the resulting alpha and
beta. Give an argument that your study is worth doing with the
smaller sample.
3. In a few sentences, describe two designs that can address
your research question. The designs must involve two different
statistical analyses. For each design, specify and justify each of
the four factors and calculate the estimated sample size youll
need. Give reasons for any parameters you need to specify for
G*Power.
Include peer-reviewed journal articles as needed to support your
responses to Part I.
Support your paper with a minimum of 5 resources. In addition
to these specified resources, other appropriate scholarly
resources, including older articles, may be included.
Length: 5 pages not including title and reference pages
ExamB/ExamB.php
<?php
// get user file
$filename = $_REQUEST['filepath'] ;
$validate = true ;
$x = array();
$y = array();

3. // var to get Point variable
$X_avg = $X_sum = 0 ;
$Y_avg = $Y_sum = 0 ;
if (!file_exists($filename)){
echo "Please correct file path." ;
}
else
// >>>>>>>>>>>>>>>>>> HERER <<<<<<<<<<<<<<<<<<<<
//

4. {
// load code file
$Points = file_get_contents($filename) ;
// get code lines
$Points_lines = explode("n", $Points);
// validate empty line
foreach ( $Points_lines as $line)
{
if(strlen($line) == 0 )
{
$validate = false ;
$validate_message = "Empty Line" ;
}
}

5. // validate pairs & Numbers
if($validate)
foreach ( $Points_lines as $line)
{
$Pairs = explode(",", $line);
if(strlen($Pairs[0]) == 0 || strlen($Pairs[1]) == 0 )
{
$validate = false ;
$validate_message = "Pairs Mismatching " ;
break;
}
else
{
if(is_numeric($Pairs[0]) &&
is_numeric($Pairs[1]) )
{

6. $validate = true ;
}
else
{
$validate = false ;
$validate_message = "Only numeric
accepted" ;
break ;
}
}
}
// validate >= 0
if($validate)
foreach ( $Points_lines as $line)
{
$Pairs = explode(",", $line);

7. if(($Pairs[0] > 0 ) && ($Pairs[1] > 0) )
{
$validate = true ;
}
else
{
$validate = false ;
$validate_message = "Only accepted value of
larger than zero" ;
break ;
}
}
if(!$validate)
{
echo "Validation Error , >> $validate_message << " ;
exit();
}

8. // >>>>>>>>>>>>>>>>>>> get N value
<<<<<<<<<<<<<<<<
$n = count($Points_lines);
$i=1 ;
foreach ( $Points_lines as $line)
{
// X values
$Pairs = explode(",", $line);
$x[$i-1] = $Pairs[0];
// Y values
$y[$i-1] = $Pairs[1];

9. // get avg for X & Y arrays
$X_sum += $x[$i-1] ;
$Y_sum += $y[$i-1] ;
// X^2 - Y^2
$X_2 += ($x[$i-1] * $x[$i-1]);
$Y_2 += ($y[$i-1] * $y[$i-1]);
// X*Y
$X_in_Y += ($x[$i-1] * $y[$i-1]) ;
$i++ ;
}

10. print_r($x);
echo "<hr>";
print_r($y);
echo "<hr>";
// X avg , Y avg
$X_avg = $X_sum/$n ;
$Y_avg = $Y_sum/$n ;
// X avg^2
$Xavgintwo = $X_avg*$X_avg;
//B One
$BOne = (($X_in_Y-($n*$X_avg*$Y_avg))/($X_2-
($n*$Xavgintwo)));
echo "B One : $BOne <br>";

11. echo "<hr>";
//B Zero
$BZero = ($Y_avg-($BOne*$X_avg));
echo "B Zero : $BZero <br>";
echo "<hr>";
//R x y
$RTwo_1 = (($n*$X_in_Y)-($X_sum*$Y_sum));
$RTwo_2_1 = (($n*$X_2)-($X_sum*$X_sum));
$RTwo_2_2 = (($n*$Y_2)-($Y_sum*$Y_sum));
$RTwoBottomSqrt = sqrt (($RTwo_2_1)*($RTwo_2_2));
$RTwoxy = ($RTwo_1/$RTwoBottomSqrt);

12. echo "R x y : $RTwoxy <br>";
//R Two
$RTwo = $RTwoxy * $RTwoxy;
echo "R Two : $RTwo <br>";
}
?>
__MACOSX/ExamB/._ExamB.php

13. ExamB/HomeB.html
Insert path location of your file:
ExamB/test.txt
16,235
51,337
122,285
72,344
__MACOSX/ExamB/._test.txt
Main Task: Application � Non-Parametric Tests
You will submit one Word document for this activity. In the
first part your activity document, provide short answers to the
following questions (250 words or less).
Part A. Questions about non-parametric procedures
1. What are the most common reasons you would select a non-
parametric test over the parametric alternative?
2. Discuss the issue of statistical power in non-parametric tests
(as compared to their parametric counterparts). Which type
tends to be more powerful? Why?
3. For each of the following parametric tests, identify the

14. appropriate non-parametric counterpart:
a. Dependent t test
b. Independent samples t test
c. Repeated measures ANOVA (one-variable)
d. One-way ANOVA (independent)
e. Pearson Correlation
Part B. SPSS Activity
In this part of the Activity you will perform the non-parametric
version of the tests you used in Week 4. In each case, assume
that you opted to use the non-parametric equivalent rather than
the parametric test. Using the data files from earlier activities,
complete the following tests and paste your results into a Word
document:
1. Week 4 Activity 6, Part A: non-parametric version of the
dependent t test
2. Week 4 Activity6, Part B: non-parametric version of the
independent t test
3. Week 4 Activity6, Part C: non-parametric version of the
single factor ANOVA
Part A. Questions about non-parametric procedures
1. What are the most common reasons you would select a non-
parametric test over the parametric alternative?
Part A.
2. Discuss the issue of statistical power in non-parametric tests
(as compared to their parametric counterparts). Which type
tends to be more powerful? Why?
3. For each of the following parametric tests, identify the
appropriate non-parametric counterpart:
a. Dependent t test

15. b. Independent samples t test
c. Repeated measures ANOVA (one-variable)
d. One-way ANOVA (independent)
e. Pearson Correlation
Part B. SPSS Activity
1. Week 4 Activity 6, Part A: non-parametric version of the
dependent t test
2. Week 4 Activity6, Part B: non-parametric version of the
independent t test
3. Week 4 Activity6, Part C: non-parametric version of the
single factor ANOVA
JUS 302
CHAPTER 9: HOMEWORK
NOTE: Please remember to restate the problem on your
homework when submitting your answers.
1. Define “power” and “effect” and illustrate the relevance of
each concept utilizing an original example. (1-2 paragraphs)
2. In 1-2 paragraphs describe when it is appropriate to set up
your alternative hypothesis as a directional as opposed to a non-
directional hypothesis.
3. An independent-measures research study uses two samples,
each with n = 8 participants. If the data produce a t statistic of t
= 2.10, what would your decision be with regard to your null
hypothesis (i.e. reject, fail to reject). To get full credit for your

16. answer you need to show how you got your critical value and
describe your rationale for your final conclusion---i.e. [show
calculation of critical value]; critical value is plus or minus
1.96, so we would fail to reject the null hypothesis because...).
Hint: you need to calculate the critical value based on the
appropriate degrees of freedom; also, in evaluating the one
tailed hypotheses, assume that the nature or direction of any
difference you find is consistent with the alternative/research
hypothesis).
a) For a two tailed hypothesis test (with alpha=.01)
b) For a one tailed hypothesis test (with alpha= .01)
c) For a two tailed hypothesis test (with alpha=.05)
d) For a one tailed hypothesis test (with alpha=.05) JUS 302
4. A psychologist has prepared an “Optimism Test” that is
administered yearly to graduating college seniors. The test
measures how each graduating class feels about its future (the
higher the score, the more optimistic the class). Last year’s
from this year’s class was selected and tested. The scores for
these seniors are 7,12,11,15,7,8,15,9, and 6, which produce a
sample mean of 10 with an estimated standard error of 1.14.
Assume that you will use the .05 level of significance. For the
two tailed test, your null hypothesis is that this year’s
graduating class is equally optimistic about the future as last
years’ graduating class; in other words there is no significant
difference between last years graduating class and this years
graduating class in terms of their level of optimism about the
future. (NOTE: using symbols you can state the null in the

17. your null hypothesis is that this year’s graduating class is
equally or less optimistic about the future than last years’
a) State an appropriate non-directional alternative hypothesis
(using symbols as well as words)
b) State an appropriate directional alternative hypothesis (using
symbols as well as words)
EXERCISE 12 Questions to be Graded
RESEARCH ARTICLE 2
Source: Voss, J. A., Good, M., Yates, B., Baun, M. M.,
Thompson, A., & Hertzog, M. (2004). Sedative music reduces
anxiety and pain during chair rest after open-heart surgery.
Pain, 112 (1–2), 197–203.
Introduction
Voss et al. (2004) conducted a study to determine the
“effectiveness of non-pharmacological complementary methods
(sedative music and scheduled rest) in reducing anxiety and
pain [sensation and distress] during chair rest” (Voss et al.,
2004, p. 197) after open-heart surgery. The subjects receiving
the treatment of sedative music had significantly less anxiety,
pain sensation, and pain distress than those subjects in the
scheduled rest and the standard care group. The researchers
recommend the use of sedative music as an adjuvant to
medication for management of anxiety and pain in postoperative
patients. The study only involved patients who had had open-
heart surgery, which limits the generalization of the findings.
Future research is needed to test the effects of music on the
anxiety and pain of different types of patients. In addition,

18. research is needed to determine the optimal length for the music
sessions and the effectiveness of repeat music sessions in
reducing anxiety and pain.
Relevant Study Results
“An experimental, pretest and posttest three-group design was
used for this randomized clinical trial. A convenience sample of
62 patients was obtained from a surgical intensive care unit at a
rural midwestern hospital over a period of 6 months in 2002. …
The planned sample size of 96 patients (30 per group plus 6 for
attrition) was based on power analysis with an estimated
medium effect size of 0.33, power 0.80, alpha = 0.05 and
repeated measures analysis of variance. However, preliminary
analyses after 62 patients were enrolled revealed significant
group differences and large effect sizes for anxiety, pain
sensation, and pain distress; thus the data collection was
concluded” (Voss et al., 2004, p. 198).
1. How large a sample was needed for the Voss et al. (2004)
study according to the power analysis? Was this the minimum
sample size needed for the study, or did the researchers allow
for sample mortality?
2. What was the sample size for the Voss et al. (2004) study?
Was this sample size adequate for this study? Provide a
rationale for your answer.
3. What effect size was used in conducting the power analysis
for this study? What effect size was found during data analysis,
and how did this affect the sample size needed for this study?
4. What power was used to conduct the power analysis in the
Voss et al. (2004) study? What amount of error exists with this
power level? Provide a rationale for your answer.

19. 5. If researchers set the power at 90% to conduct their power
analysis, would there be less or more chance of a Type II error
than setting the power at 80%? Provide a rationale for your
answer.
6. If researchers set the alpha (α) for their study at 0.001 versus
0.05, would they need a smaller or larger sample size? Provide a
rationale for your answer.
7. In the discussion section of the research article, the authors
stated that sedative music had a large effect size when
compared to both usual chair rest (>1.0) and scheduled chair
rest (>0.9). Furthermore, scheduled chair rest when compared
with usual chair rest did not result in significantly less anxiety,
pain sensation, or pain distress, but the differences were in the
expected direction with small to medium effects (0.20 to 0.45).
Why is this information important for future research?
8. Based on the information provided in Question 7, what effect
size(s) would researchers use in conducting a similar study?
Provide a rationale for your answer.
9. If a researcher conducted a two-tailed t-test versus a one-
tailed t-test, would they need a smaller or larger sample size?
Provide a rationale for your answer.
10. Should the findings from the Voss et al. (2004) study be
used in clinical practice? Provide a rationale for your answer.