SIMULATED RESEARCH PAPER

Simulated Research Paper

Simulated Research Paper

Computation 1: Chapter 6

Problem # 5: Solution

In descriptive statistics, a quartile is each of the three values ??that divide the sorted data into 4 equal parts, so that each part represents one fourth of the sample population.

Statistics

OVERALL COLLEGE GPA

MAJOR AREA GPA

GRE SCORE ON QUANTATIVE

N

Valid

50

50

50

Missing

0

0

0

Quartiles

25

3.3475

3.6275

640.00

50

3.5500

3.8150

685.00

75

3.7100

3.9700

740.00

Quartile is calculated as 4-quantile

The 1st quartile divides the bottom 25% of the data;

The 2nd quartile is the median of the series;

The 3rd quartile separates the lower 75% of the data.

The difference between the 3 rd quartile and 1st quartile is called inter-quartile range, which is a dispersion criterion of the series.

Solution

One-Sample Test

Test Value = 33

tdfSig. (2-tailed)Mean Difference95% Confidence Interval of the Difference

LowerUpper

Age-2.737536.006-1.655-2.84-.47



Computation 4

Chapter 12

Problem # 5

Using the grades.sav data, create a correlation matrix using year, gpa, and grade. Using regression, predict grade from year and grade from gpa.

Correlation Matrix using year, gpa, and grade

Correlations

Year in schoolgpagrade

Year in schoolPearson Correlation1-.083-.003

Sig. (1-tailed).200.487

N105105105

gpaPearson Correlation-.0831.476**

Sig. (1-tailed).200.000

N105105105

gradePearson Correlation-.003.476**1

Sig. (1-tailed).487.000

N105105105

**. Correlation is significant at the 0.01 level (1-tailed).

The 1-tailed correlation results shows that there is a strongly weak significance between year and GPA as well as

Computation 2: Chapter 9

Problem # 2: Solution

ANOVA Table

Sum of Squares

d.f.

Mean Square

F

Sig.

Final * Year in school

Between Groups

(Combined)

37.165

3

12.388

.192

.902

Linearity

5.248

1

5.248

.081

.776

Deviation from Linearity

31.917

2

15.959

.247

.782

Within Groups

6525.025

101

64.604

Total

6562.190

104

Measures of Association

R

R Squared

Eta

Eta Squared

Final * Year in school

-.028

.001

.075

.006

ANOVA Table

Sum of Squares

d.f.

Mean Square

F

Sig.

Final * Section

Between Groups

(Combined)

183.752

2

91.876

1.469

.235

Linearity

180.015

1

180.015

2.879

.093

Deviation from Linearity

3.737

1

3.737

.060

.807

Within Groups

6378.438

102

62.534

Total

6562.190

104

Measures of Association

R

R Squared

Eta

Eta Squared

Final * Section

-.166

.027

.167

.028

Computation 3: Chapter 11

Problem # 5: Solution

In this section we will see how to test the null hypothesis from two means from two samples (or subgroups) independent. We will actually judge whether two means are equal in population-Based on the result of the comparison between these two samples. The technique used is called t-test for independent samples (Independent sample t test).

Independent Samples Test

Levene's Test for Equality of Variances

t-test for Equality of Means

F

Sig.

t

df

Sig. (2-tailed)

Mean Difference

Std. Error Difference

95% Confidence Interval of the Difference

Lower

Upper

age

Equal variances assumed

1.159

.282

-2.028

535

.043

-2.502

1.234

-4.925

-.078

Equal variances not assumed

-1.984

417.543

.048

-2.502

1.261

-4.980

-.023

NUMBER OF YEARS IN SCHOOL

Equal variances assumed

.678

.411

-1.886

535

.060

-.200

.106

-.408

.008

Equal variances not assumed

-1.898

460.258

.058

-.200

.105

-.407

.007

income

Equal variances assumed

.219

.640

1.568

535

.118

.186

.119

-.047

.419

Equal variances not assumed

1.563

446.563

.119

.186

.119

-.048

.420

MEAN CLOSENESS RATING

Equal variances assumed

2.808

.094

4.155

535

.000

.5051

.1216

.2663

.7440

Equal variances not assumed

4.187

462.717

.000

.5051

.1206

.2681

.7422

HELPER MEAN RATING OF CONTROLLABILITY

Equal variances assumed

.035

.852

-3.596

535

.000

-.5432

.1511

-.8399

-.2464

Equal variances not assumed

-3.572

440.945

.000

-.5432

.1521

-.8420

-.2443

MEAN RATING OF FOUR ANGER QUESTIONS

Equal variances assumed

.642

.423

-2.849

535

.005

-.3848

.1351

-.6501

-.1194

Equal variances not assumed

-2.858

456.106

.004

-.3848

.1346

-.6493

-.1202

MEAN RATING OF 3 HELPER COPING QUESTIONS

Equal variances assumed

.015

.903

2.748

535

.006

.2939

.1069

.0838

.5040

Equal variances not assumed

2.753

453.777

.006

.2939

.1068

.0841

.5037

SYMPATHY MEASURE DELETING PITY

Equal variances assumed

1.764

.185

5.107

535

.000

.57425

.11245

.35336

.79514

Equal variances not assumed

5.042

431.316

.000

.57425

.11390

.35037

.79812

HELPER MEAN SEVERITY RATING

Equal variances assumed

2.346

.126

3.197

535

.001

.4422

.1383

.1705

.7139

Equal variances not assumed

3.130

418.234

.002

.4422

.1413

.1645

.7199

MEAN OF 14 EMPATHY QUESTIONS

Equal variances assumed

.159

.690

7.681

535

.000

.60468

.07873

.45003

.75934

Equal variances not assumed

7.742

463.101

.000

.60468

.07810

.45121

.75816

MEAN OF 14 EFFICACY MEASURES

Equal variances assumed

.718

.397

2.927

535

.004

.24725

.08447

.08132

.41318

Equal variances not assumed

2.942

458.641

.003

.24725

.08405

.08209

.41242

MEAN OF HELPER/RECIPIENT LNZHELP

Equal variances assumed

3.077

.080

4.285

535

.000

.35002

.08169

.18955

.51050

Equal variances not assumed

4.189

416.542

.000

.35002

.08355

.18579

.51425

MEAN OF HELPER/RECIPIENT ZQUALITY HELP

Equal variances assumed

.077

.782

3.108

535

.002

.23896

.07689

.08792

.38999

Equal variances not assumed

3.098

446.070

.002

.23896

.07714

.08735

.39056

COMBINED HELP MEASURE--QUANTITY & QUALITY

Equal variances assumed

.425

.515

4.620

535

.000

.29449

.06374

.16928

.41970

Equal variances not assumed

4.558

430.328

.000

.29449

.06461

.16751

.42147

Problem # 7: Solution

One-Sample Test

Test Value = 33

t

df

Sig. (2-tailed)

Mean Difference

95% Confidence Interval of the Difference

Lower

Upper

Age

-2.737

536

.006

-1.655

-2.84

-.47

year and grade. However there is a little stronger relation between GPA and Grade that is 0.476.

The negative value shows that there is negative relation between year and GPA and year and Grade. However, the positive Pearson Correlation between GPA and Grade shows there is positive relation between them, which means that as the GPA increases, ...