TUGASAN KUMPULAN :

KUMPULAN RAUDATUL JANNAH

AHLI KUMPULAN :

1. ROSNAH BINTI MD ZAIN - KORELASI

2. ROSAZWANI BT. HJ MUHAMMAD - T-TEST BERKEMBAR

3. JASNIDA BT. ABU BAKAR - ANOVA

4. NORAZLENA BT. AWANG - REGRASI & KHI KUASA DUA

5. FATEN NAJUA BT. AHMAD - T-TEST

LATIHAN MEMAHAMI ANALISIS STATISTIK

ANALISIS UJIAN KORELASI

TAJUK JURNAL :

“ Effect of Self-Esteem in the Relationship between Stress and Substance Abuse among

Adolescents: A Mediation Outcome “

Disediakan oleh :

ROSNAH BINTI MD ZAIN

Substance abuse was measured with the Drug Abuse

Screening Test

Stress was measured with the Perceived Stress Scale

Self-esteem was measured with the Rosenberg Self-esteem

scale.

METODS

ISSUES

1) What is the level of stress, self-esteem and substance abuse?

2) What is the relationship between stress, self-esteem and substance

abuse?

3) Does self-esteem mediate the relationship between stress and

substance abuse?

OBJECTIVE

The present study assessed the mediating effect of self-esteem in the

relationship between stress and substance abuse among adolescents.

HIPOTESIS

There is a relationship between self-esteem effects of stress and drugs

abuse among adolescents.

ANALISIS KORELASI

RESULT

The study ascertained a negative and large correlation (r=-.538,

p<.01) between stress and self-esteem, similar results (r=-

.536,p<.01) was found between self-esteem and substance abuse

and a positive and medium correlation (r=.360,p<.01) was found

between stress and substance abuse. Self-esteem partially

mediated the relationship between stress and substance abuse.

So, hypothesis null was accepted.

INTERPRESTASI

ANALISIS T-TEST BERKEMBAR

TAJUK JURNAL :

“THE IMPACT OF CHILD CENTERED PLAY

THERAPY TRAINING ON ATTITUDE,

KNOWLEDGE AND SKILLS”

Disediakan oleh :

ROSAZWANI BT. HJ. MUHAMMAD

T-test Berkembar yang mana menggunakan mix method

iaitu qualitative dan quantitative

- Quantitative adalah menggunakan data yang dikutip

- Qualitative adalah menggunakan interview demi

mengukuhkan data yang dikutip

JENIS UJIAN ANALISIS T-TEST BERKEMBAR

PERSOALAN

1. Apakah kesan latihan Child Centered Play Therapy

terhadap tingkah laku siswazah tentang kanak- kanak,

interaksi dengan kanak- kanak dan pengetahuan serta

kemahiran tentang play therapy?

2. Apakah persepsi siswazah tentang struktur dan kandungan dalam pengenalan

kursus play therapy?

OBJEKTIF

Untuk mengenal pasti kesan Child Centered Play Therapy siswazah dari segi

kelakuan, pengetahuan dan kemahiran.

HIPOTESIS

Tidak terdapat perbezaan terhadap kelakuan, pengetahuan dan kemahiran siswazah

dalam pra ujiandan pasca ujian.

ANALISIS T-TEST BERKEMBAR

Table 5.1 Pre and Post Test Scores on the Revised Play Therapy Attitude-

Knowledge- Skills Survey

(n = 13)

----------------------------------------------------------------------------------------

Pretest Posttest

Subscale M SD M SD

Attitude 4.15 .26 4.53 .26

Knowledge 2.34 .77 4.02 .52

Skills 2.38 .68 3.99 .41

-----------------------------------------------------------------------------------------

P < .001

KEPUTUSAN ANALISIS T-TEST BERKEMBAR

Keputusan Ujian T Berkembar ke atas tahap kelakuan,

pengetahuan dan kemahiran siswazah dalam pra ujian dan

pasca ujian menunjukkan (t (13) = -7.74, p<.001. Ini bermakna

hipotesis nul berjaya ditolak. Maka, keputusan yang diperolehi

menunjukkan terdapat perbezaan yang signifikan antara ujian

pra dan pasca ujian bagi aspek tersebut. Didapati bahawa

tahap kelakuan, pengetahuan dan kemahiran telah meningkat

selepas intervensi program ini.

INTERPRETASI ANALISIS T-TEST BERKEMBAR

ANALISIS UJIAN ANOVA

Tajuk Jurnal :

Comparing student success between

developmental math courses offered

online, blended, and face-to-face.

Disediakan oleh :

JASNIDA BT. ABU BAKAR

TYPE OF TEST

This study used quantitative research methodologies

Comparisons between learning environments on

continuous outcomes (unit tests, final exam, course

average) were made using one-way ANOVA, with

learning environment as the factor, with three levels

(Face-to-face, Blended, and Online).

Tukey’s HSD was applied following significant main

effects to identify pairwise differences.

ISSUES

1. Does the type of learning environment relate to successful course performance as

measured by test, final exam, and course grade?

2. Does the effect of course performance depend upon attrition?

OBJECTIVE

This study used quantitative research methodologies to compare student success in

different learning environments

HYPOTESIS

There is a different type of learning environment relate to successful course

performance as measured by test, final exam, and course grade?

There is a different effect of course performance depend upon attrition?

ANALISIS UJIAN ANOVA

RESULT ANOVA Table 1

IACE Scores for All Participants by Learning Environment

N Number

Correct

SD for Number

Correct

Percentage SD for

Percentage

All Subjects 167 25.3 14.72 52.6% 30.69

Face-to-face 58 28.9 10.83 60.2% 22.61

Blended 46 22.0 16.61 45.8% 34.59

Online 63 24.3 15.83 50.7% 33.02

Note. The N column lists the number of subjects in the group. The

number correct is out of 48 problems. For Fall 2009, the success

rate across all 104 Intermediate Algebra courses at this institution

was 54.7%. The standard deviation (SD) for both the number correct

and percentage is provided.

Students in the blended learning environment had the lowest mean

scores on all assessments.

For illustrative purposes, effect sizes were calculated for the Course

Average comparisons. The effect size for the face-to-face vs. online

difference was 0.17 favoring the face-to-face environment. For the

face-to-face vs. blended comparison, the effect size was 0.53, also

favoring the face-to-face environment. The online vs. blended

comparison effect size was 0.31, favoring the online environment.

INTERPRETASI ANOVA

Table 2

Mean and Standard Deviation Percent Correct on Unit Tests, IACE, and Course Average

by Learning Environment (Complete Dataset N = 167)

Face-toface

(N = 58)

Blended (N = 46) Online (N = 63)

F(2, 164)

p

Pairwise tests of

significanceh

Unit Test

#1a

70.1 (21.4) 67.9 (32.1) 77.6 (24.6) 2.21 0.113

Unit Test #2b

88.7 (14.7) 69.5 (34.5) 75.0 (32.5) 6.54 0.002* F>B;F>O

Unit Test

#3c

50.4 (23.1) 45.4 (32.2) 59.3 (30.3) 3.39 0.036* O>B

Unit Test #4d

67.3 (22.7) 55.6 (33.5) 64.2 (34.1) 2.00 0.138

Unit Test

#5e

83.4 (20.2) 62.2 (41.1) 78.2 (35.4) 5.68 0.004* F>B; O>B

Unit Test #6f

63.8 (26.9) 52.8 (38.4) 64.7 (37.7) 1.82 0.165

Unit Test

#7g

75.5 (27.0) 54.4 (43.3) 65.0 (43.5) 3.86 0.023* F>B

IACE 60.2 (22.6) 45.8 (34.6) 50.7 (33.0) 3.13 0.046* F>B

Course Average 68.1 (18.7) 54.5 (32.0) 63.9 (28.5) 3.40 0.036* F>B

Note. *p < 0.05 for main effect of Learning

Environment.aFactoring, bFunction notation and

operations, cRational Expressions, dRadicals, eComplex and

Imaginary Numbers, fSolving Quadratic Equations, gParabolas and Circles, hPairwise significance tests via

Tukey’s HSD, p < 0.05.

The number of students earning passing grades was not

significantly different between the three learning

environments: Face-to-face 59%, Blended 48%, and Online

65%, !2 (2, N = 167) = 3.26; p = 0.20.

Table 3

Mean and Standard Deviation Percent Correct on Unit Tests, IACE, and Course

Average by Learning Environment (Attrition Adjusted Dataset N=134)

Face-toface

(N = 54)

Blended (N = 32) Online (N = 48)

F(2, 131)

p

Pairwise tests of

significanceh

Unit Test

#1a

72.2 (19.5) 79.3 (21.1) 85.7 (11.4) 7.53 0.001* O>F

Unit Test #2b

90.7 (8.8) 86.6 (12.8) 88.4 (10.4) 1.63 0.200

Unit Test

#3c

52.7 (21.5) 59.8 (26.1) 70.4 (21.5) 7.71 0.001* O>F

Unit Test

#4d

70.4 (19.0) 72.2 (20.7) 78.2 (20.1) 2.07 0.130

Unit Test #5e

87.5 (13.3) 83.9 (20.4) 92.4 (15.3) 2.84 0.062

Unit Test

#6f

67.2 (24.1) 73.9 (22.6) 81.6 (21.7) 5.04 0.008* O>F

Unit Test

#7g

80.6

(19.7)

78.2

(28.3)

81.4

(31.9)

0.14 0.869

IACE 64.7

(16.0)

65.8

(19.4)

66.5

(19.1)

0.13 0.878

Course 71.6

(13.3)

73.1

(15.8)

78.1

(10.1)

3.37 0.038* O>F

Note. *p < 0.05 for main effect of Learning Environment.aFactoring, bFunction notation and operations, cRational Expressions, dRadicals, eComplex and Imaginary Numbers, fSolving Quadratic Equations, gParabolas and Circles.hPairwise significance tests via Tukey’s HSD, p <

0.05

One discrepancy among the age and gender controlled analyses was

that the Online vs. Face-to-face difference was no longer statistically

significant after control of multiple comparisons by Tukey’s HSD

(difference = 5.3 SE = 2.8, t = 1.93; adjusted p-value = 0.135).

Among those students who completed the course, the number of

students earning a passing course grade was significantly different

between the three learning environments: Faceto-face 63%, blended

69%, and online 85%, !2 (2, N = 134) = 6.69; p = 0.04. However, more

students in the face-to-face environment completed the course (93%)

compared to students in the blended (70%) and online (76%) courses,

!2 (2, N = 167) = 10.01; p = 0.007.

ANALISIS KORELASI, REGRESI

& KHI KUASA DUA

TAJUK JURNAL :

“BIG FIVE PERSONALITY TRAITS –

A TOOL FOR MANAGING STRESS” (Tactful Management Research Journal,

Vol. 1, Issue 2, Nov. 2012)

Disediakan oleh :

NORAZLENA BT. AWANG (817917)

METOD

Jumlah penduduk mengambil bahagian : 600 konstabel

polis Balai Polis Cawangan Jenayah Negeri Tamilnadu

2 jenis instrumen

i) Police Stress Inventory(PSI) – Pienaar &

Rothmann (2006)

ii) NEO Five Factor Inventory ( NEO FFI)

Skala Likert

Jadual 1: Profil Demografi

Jadual 2:

Perhubungan antara Tekanan Pekerjaan

dan Big Five Trait Personaliti

Extraversion

Keterbukaan

Bersetuju

Sifat berhati-hati

Stress kerja

Keputusan ini menunjukkan bahawa jumlah tekanan kerja yang signifikan dengan extraversion

(r=0.849, kesan yang kuat), keterbukaan (r=0.886, kesan yang kuat), agreeableness (r=0.859,

Kesan yang kuat), sifat berhati-hati (r=0.639, kesan sederhana) dan dengan stres kerja

(r=0.401, kesan sederhana).

Small : r=.10 to .29

Medium : r=.30 to .49

Large : r=.50 to 1.0

OBJEKTIF :

Menentukan faktor personaliti yang

menjadi peramal kepada tekanan kerja.

PERSOALAN :

Adakah terdapat pengaruh personaliti

terhadap tekanan kerja?

HIPOTESIS :

Sifat-sifat personaliti yang menjadi

faktor peramal kepada tekanan kerja

REGRESSION:

Tekanan

Kerja Personaliti

Jadual 3 :

Analisis Regresi Antara Tekanan

Pekerjaan dan Big Five Trait Personaliti

Hasil kajian menunjukkan terdapat pengaruh antara traits personaliti

dalam perkhidmatan terhadap tekanan, iaitu (r(70)= .837, p>.05). Ini

bermakna, hipotesis nul berjaya diterima.

ANALISIS KHI KUASA DUA

OBJEKTIF :

Untuk mengenalpasti perkaitan antara

tekanan kerja dengan kelompok umur,

jantina, status perkahwinan, tempoh

berkhidmat dan pendapatan bulanan .

PERSOALAN :

Adakah terdapat perkaitan antara Profil

Demografi, personaliti terhadap tekanan

kerja?

HIPOTESIS :

Tidak Terdapat perkaitan antara tekanan

kerja dengan kelompok mengikut umur,

jantina, status perkahwinan, tempoh

berkhidmat dan pendapatan bulanan.

Tekanan

Kerja

Profil Demografi

Personaliti

Jadual 4 :

Khi Kuasa Dua antara Profil Demografi

dan Tekanan Pekerjaan

Dari jadual di atas menunjukkan bahawa semua nilai yang ketara

adalah kurang daripada 0.05 , oleh itu semua detail demografi

Konstabel Polis adalah signifikan antara tekanan pekerjaan.

Jadual 5 :

Khi Kuasa Dua antara Profil Demografi

dan Personaliti

Dari jadual di atas menunjukkan bahawa semua nilai

yang ketara kurang daripada 0.05, oleh itu semua

butir-butir demografi konstabel polis ketara kaitan

antara personaliti.

Kajian ini bertujuan untuk mengetahui hubungan antara

personaliti dan tekanan kerja antara strategi menghadapi

penyakit.

Hipotesis 1 menyatakan bahawa semua profil demografi

konstabel polis signifikan dengan tekanan pekerjaan.

Hipotesis 2 menyatakan bahawa semua profil demografi

konstabel polis signifikan dengan personaliti.

Hipotesis 3 menyatakan bahawa tekanan dan personaliti

sifat-sifat pekerjaan yang positif.

PERBINCANGAN & KESIMPULAN

Personaliti dapat meramalkan tekanan pekerjaan. Semua ciri-ciri

personaliti yang sangat berguna untuk descript tekanan polis.

Selain itu, ciri-ciri personaliti yang lebih meramalkan kuasa

daripada mana-mana pembolehubah konteks lain. Keputusan ini

menyokong keperluan untuk mengambil kira ciri-ciri personaliti

menyedari dan bergerak ke arah tekanan polis.

Akhirnya penyelidikan dalam tekanan polis perlu pergi jauh ke

dalam pembolehubah kontekstual seperti permintaan pekerjaan,

kekurangan atau sumber dan tekanan polis, keperluan fizikal dan

psikologi, dan peranan kecerdasan emosi dalam mengurangkan

tekanan.

Kajian ini tertumpu di selatan Tamilnadu konstabel polis. Dalam

pelbagai masa depan penyelidikan perlu dilakukan di semua

dilakukan di semua peringkat peribadi polis termasuk pegawai

peringkat tertinggi.

PERBINCANGAN & KESIMPULAN

Using the Student’s t-test

with extremely small

sample sizes

Disediakan oleh :

FATEN NAJUA BT. AHMAD

ANALISIS T-TEST

Using the Student’s t-test with

extremely small sample sizes

(Using the Student’s t-test with

extremely small sample sizes – Volume

18, Number 10, August 2013)

Disediakan oleh :

FATEN NAJUA BT. AHMAD

METHOD

Simulations were conducted to determine the statistical power and Type I

error rate of the onesample and two-sample t-tests. Sampling was done

from a normally distributed population with a mean of 0 and a standard

deviation of 1.

One of the two distributions was shifted with a value of Dwith respect to 0.

A sample was drawn from the population, and submitted to either the one-

sample t-test with a reference value of zero, or to the two-sample t-test

for testing the null hypothesis that the populations have equal means.

The simulations were carried out for Ds between 0 (i.e., the null

hypothesis holds) and 40 (i.e., the alternative hypothesis holds with an

extremely large effect), and for N = 2, N = 3, and N = 5. In the twosample

t-test, both samples were of equal size (i.e., N = M). A p value below 0.05

was considered statistically significant. All analyses were two-tailed. Each

case was repeated 100,000 times.

OBJECTIVE

1. behavior of the Welch test and a rank-transformation prior to conducting the t-test (t-testR).

2. Simulations were conducted to determine the statistical power and Type I error rate of the one

sample and two-sample t-tests.

3. Sampling was done from a normally distributed population with a mean of 0 and a standard

deviation of 1. One of the two distributions was shifted with a value of D with respect to 0. A sample

was drawn from the population, and submitted to either the one-sample t-test.

ISSUES

1.The present simulation study estimated the type 1 error rate and statistical power of the one- and

two sample t tests for normally distributed populations and various distortions such as unequal

sample sizes , unequal variences, the combination of unequel sample sizes and unequel variences

and lognormal population distribution

HIPOTESIS

There is difference type one error rate and statistical power of the one- and two sample t tests for

normally distributed populations.

RESULTS

DISCUSSION

The present simulation study showed that there is no fundamental objection to using a

regular t-test with extremely small sample sizes. Even a sample size as small as 2 did not

pose problems. In most of the simulated cases, the Type I error rate did not exceed the

nominal value of 5%. A paired t-test is also feasible with extremely small sample sizes,

particularly when the within-pair correlation coefficient is high.

A high Type I error rate was observed for unequal variances combined with unequal sample

sizes (withthe smaller sample drawn from the high variance population), and for a one-

sample t-test applied to nonnormally distributed data. The simulations further clarified that

when the sample size is extremely small,

Type II errors can only be avoided if the effect size is extremely large. In other words,

conducting a t-test with extremely small samples is feasible, as long as the true effect size is

large

The fact that the t-test functions properly for extremely small sample sizes may come as no

surprise to the informed reader. In fact, William Sealy Gosset (working under the pen

name“Student”) developed the t-test especially for small sample sizes (Student, 1908; for

reviews see Box, 1987; Lehmann, 2012; Welch, 1958; Zabell, 2008), a condition where the

traditional ztest provides a high rate of false positives. Student himself verified his t-

distribution on anthropometric data of 3,000 criminals, which he randomly divided into 750

samples each having a sample size of 4.

SEKIAN, TERIMA KASIH.