SlideShare a Scribd company logo
1 of 12
11
The t testThe t test
22
ApplicationsApplications
 To compare the mean of a sample withTo compare the mean of a sample with
population mean.population mean.
 To compare the mean of one sampleTo compare the mean of one sample
with the mean of another independentwith the mean of another independent
sample.sample.
 To compare between the valuesTo compare between the values
(readings) of one sample but in 2(readings) of one sample but in 2
occasions.occasions.
33
1.Sample mean and population1.Sample mean and population
meanmean
 The general steps of testing hypothesis must beThe general steps of testing hypothesis must be
followed.followed.
 Ho: Sample mean=Population mean.Ho: Sample mean=Population mean.
 Degrees of freedom = n - 1Degrees of freedom = n - 1
SE
X
t
−
−
=
µ
44
ExampleExample
The following data represents hemoglobin values inThe following data represents hemoglobin values in
gm/dl for 10 patients:gm/dl for 10 patients:
Is the mean value for patients significantly differIs the mean value for patients significantly differ
from the mean value of general populationfrom the mean value of general population
(12 gm/dl) . Evaluate the role of chance.(12 gm/dl) . Evaluate the role of chance.
10.510.5 99 6.56.5 88 1111
77 7.57.5 8.58.5 9.59.5 1212
55
SolutionSolution
 Mention all steps of testing hypothesis.Mention all steps of testing hypothesis.
Then compare with tabulated value, for 9 df, and 5% level ofThen compare with tabulated value, for 9 df, and 5% level of
significance. It is = 2.262significance. It is = 2.262
The calculated value>tabulated value.The calculated value>tabulated value.
Reject Ho and conclude that there is a statistically significant differenceReject Ho and conclude that there is a statistically significant difference
between the mean of sample and population mean, and thisbetween the mean of sample and population mean, and this
difference is unlikely due to chance.difference is unlikely due to chance.
352.5
10
80201.1
1295.8
−=
−
=t
66
77
2.Two independent samples2.Two independent samples
The following data represents weight in Kg for 10The following data represents weight in Kg for 10
males and 12 females.males and 12 females.
Males:Males:
Females:Females:
80 75 95 55 60
70 75 72 80 65
60 70 50 85 45 60
80 65 70 62 77 82
88
2.Two independent samples, cont.2.Two independent samples, cont.
 Is there a statistically significant difference betweenIs there a statistically significant difference between
the mean weight of males and females. Let alpha =the mean weight of males and females. Let alpha =
0.010.01
 To solve it follow the steps and use this equation.To solve it follow the steps and use this equation.
)
11
(
2
)1()1(
2121
2
22
2
11
21
nnnn
SnSn
XX
t
+
−+
−+−
−
=
−
−
99
ResultsResults
 Mean1=72.7 Mean2=67.17Mean1=72.7 Mean2=67.17
 Variance1=128.46 Variance2=157.787Variance1=128.46 Variance2=157.787
 Df = n1+n2-2=20Df = n1+n2-2=20
 t = 1.074t = 1.074
 The tabulated t, 2 sides, for alpha 0.01 is 2.845The tabulated t, 2 sides, for alpha 0.01 is 2.845
 Then accept Ho and conclude that there is noThen accept Ho and conclude that there is no
significant difference between the 2 means. Thissignificant difference between the 2 means. This
difference may be due to chance.difference may be due to chance.
 P>0.01P>0.01
1010
3.One sample in two occasions3.One sample in two occasions
 Mention steps of testing hypothesis.Mention steps of testing hypothesis.
 The df here = n – 1.The df here = n – 1.
n
sd
d
t
−
=
1
)( 2
2
−
−
=
∑
∑
n
n
d
d
sd
1111
Example: Blood pressure of 8Example: Blood pressure of 8
patients, before & after treatmentpatients, before & after treatment
BP beforeBP before BP afterBP after dd dd22
180180 140140 4040 16001600
200200 145145 5555 30253025
230230 150150 8080 64006400
240240 155155 8585 72257225
170170 120120 5050 25002500
190190 130130 6060 36003600
200200 140140 6060 36003600
165165 130130 3535 12251225
Mean d=465/8=58.125Mean d=465/8=58.125 ∑∑d=465d=465 ∑∑dd22
=29175=29175
1212
Results and conclusionResults and conclusion
 t=9.387t=9.387
 Tabulated t (df7), with level of significanceTabulated t (df7), with level of significance
0.05, two tails, = 2.360.05, two tails, = 2.36
 We reject Ho and conclude that there isWe reject Ho and conclude that there is
significant difference between BP readingssignificant difference between BP readings
before and after treatment.before and after treatment.
 P<0.05.P<0.05.

More Related Content

What's hot

Anova (f test) and mean differentiation
Anova (f test) and mean differentiationAnova (f test) and mean differentiation
Anova (f test) and mean differentiationSubramani Parasuraman
 
Emil Pulido on Quantitative Research: Inferential Statistics
Emil Pulido on Quantitative Research: Inferential StatisticsEmil Pulido on Quantitative Research: Inferential Statistics
Emil Pulido on Quantitative Research: Inferential StatisticsEmilEJP
 
Analysis of Variance (ANOVA), MANOVA: Expected variance components, Random an...
Analysis of Variance (ANOVA), MANOVA: Expected variance components, Random an...Analysis of Variance (ANOVA), MANOVA: Expected variance components, Random an...
Analysis of Variance (ANOVA), MANOVA: Expected variance components, Random an...Satish Khadia
 
Correlation & Regression Analysis using SPSS
Correlation & Regression Analysis  using SPSSCorrelation & Regression Analysis  using SPSS
Correlation & Regression Analysis using SPSSParag Shah
 
Chi square test final
Chi square test finalChi square test final
Chi square test finalHar Jindal
 
To Interpret the SPSS table of Independent sample T-Test, Paired sample T-Tes...
To Interpret the SPSS table of Independent sample T-Test, Paired sample T-Tes...To Interpret the SPSS table of Independent sample T-Test, Paired sample T-Tes...
To Interpret the SPSS table of Independent sample T-Test, Paired sample T-Tes...Ranjani Balu
 
Variance component analysis by paravayya c pujeri
Variance component analysis by paravayya c pujeriVariance component analysis by paravayya c pujeri
Variance component analysis by paravayya c pujeriParavayya Pujeri
 
Testing hypothesis
Testing hypothesisTesting hypothesis
Testing hypothesisAmit Sharma
 
Inferential statistics quantitative data - anova
Inferential statistics   quantitative data - anovaInferential statistics   quantitative data - anova
Inferential statistics quantitative data - anovaDhritiman Chakrabarti
 
ANOVA TEST by shafeek
ANOVA TEST by shafeekANOVA TEST by shafeek
ANOVA TEST by shafeekShafeek S
 
F test and ANOVA
F test and ANOVAF test and ANOVA
F test and ANOVAParag Shah
 

What's hot (18)

Z-Test with Examples
Z-Test with ExamplesZ-Test with Examples
Z-Test with Examples
 
Anova (f test) and mean differentiation
Anova (f test) and mean differentiationAnova (f test) and mean differentiation
Anova (f test) and mean differentiation
 
Emil Pulido on Quantitative Research: Inferential Statistics
Emil Pulido on Quantitative Research: Inferential StatisticsEmil Pulido on Quantitative Research: Inferential Statistics
Emil Pulido on Quantitative Research: Inferential Statistics
 
Chi square
Chi squareChi square
Chi square
 
Analysis of Variance (ANOVA), MANOVA: Expected variance components, Random an...
Analysis of Variance (ANOVA), MANOVA: Expected variance components, Random an...Analysis of Variance (ANOVA), MANOVA: Expected variance components, Random an...
Analysis of Variance (ANOVA), MANOVA: Expected variance components, Random an...
 
Correlation & Regression Analysis using SPSS
Correlation & Regression Analysis  using SPSSCorrelation & Regression Analysis  using SPSS
Correlation & Regression Analysis using SPSS
 
Student t t est
Student t t estStudent t t est
Student t t est
 
Assumptions of ANOVA
Assumptions of ANOVAAssumptions of ANOVA
Assumptions of ANOVA
 
Chi square test final
Chi square test finalChi square test final
Chi square test final
 
To Interpret the SPSS table of Independent sample T-Test, Paired sample T-Tes...
To Interpret the SPSS table of Independent sample T-Test, Paired sample T-Tes...To Interpret the SPSS table of Independent sample T-Test, Paired sample T-Tes...
To Interpret the SPSS table of Independent sample T-Test, Paired sample T-Tes...
 
Variance component analysis by paravayya c pujeri
Variance component analysis by paravayya c pujeriVariance component analysis by paravayya c pujeri
Variance component analysis by paravayya c pujeri
 
Chi square test
Chi square testChi square test
Chi square test
 
Analysis of variance anova
Analysis of variance anovaAnalysis of variance anova
Analysis of variance anova
 
Testing hypothesis
Testing hypothesisTesting hypothesis
Testing hypothesis
 
Inferential statistics quantitative data - anova
Inferential statistics   quantitative data - anovaInferential statistics   quantitative data - anova
Inferential statistics quantitative data - anova
 
ANOVA TEST by shafeek
ANOVA TEST by shafeekANOVA TEST by shafeek
ANOVA TEST by shafeek
 
F test and ANOVA
F test and ANOVAF test and ANOVA
F test and ANOVA
 
Analysis of variance
Analysis of varianceAnalysis of variance
Analysis of variance
 

Viewers also liked

Writing a research protocol 2011
Writing a research protocol 2011Writing a research protocol 2011
Writing a research protocol 2011Forensic Pathology
 
Writing a research protocol 2011
Writing a research protocol 2011Writing a research protocol 2011
Writing a research protocol 2011Forensic Pathology
 
Stat3 central tendency & dispersion
Stat3 central tendency & dispersionStat3 central tendency & dispersion
Stat3 central tendency & dispersionForensic Pathology
 
Haemodynamic disorders , thromboembolism and shock by Dr Nadeem (RMC)
Haemodynamic disorders , thromboembolism and shock by Dr Nadeem (RMC)Haemodynamic disorders , thromboembolism and shock by Dr Nadeem (RMC)
Haemodynamic disorders , thromboembolism and shock by Dr Nadeem (RMC)Hassan Ahmad
 
Hemodynamic disorders, thrombosis and shock (practical pathology)
Hemodynamic disorders, thrombosis and shock (practical pathology)Hemodynamic disorders, thrombosis and shock (practical pathology)
Hemodynamic disorders, thrombosis and shock (practical pathology)Mohaned Lehya
 

Viewers also liked (15)

Exercise 1 12 no solution
Exercise 1 12 no solutionExercise 1 12 no solution
Exercise 1 12 no solution
 
Hemodynamics disorders
Hemodynamics disorders Hemodynamics disorders
Hemodynamics disorders
 
Prac ex'cises 3[1].5
Prac ex'cises 3[1].5Prac ex'cises 3[1].5
Prac ex'cises 3[1].5
 
Prac excises 3[1].5
Prac excises 3[1].5Prac excises 3[1].5
Prac excises 3[1].5
 
Stat6 chi square test
Stat6 chi square testStat6 chi square test
Stat6 chi square test
 
Some statistical defenition
Some statistical defenitionSome statistical defenition
Some statistical defenition
 
Writing a research protocol 2011
Writing a research protocol 2011Writing a research protocol 2011
Writing a research protocol 2011
 
Writing a research protocol 2011
Writing a research protocol 2011Writing a research protocol 2011
Writing a research protocol 2011
 
Exercise 1 12 no solution
Exercise 1 12 no solutionExercise 1 12 no solution
Exercise 1 12 no solution
 
Stat3 central tendency & dispersion
Stat3 central tendency & dispersionStat3 central tendency & dispersion
Stat3 central tendency & dispersion
 
Haemodynamic disorders , thromboembolism and shock by Dr Nadeem (RMC)
Haemodynamic disorders , thromboembolism and shock by Dr Nadeem (RMC)Haemodynamic disorders , thromboembolism and shock by Dr Nadeem (RMC)
Haemodynamic disorders , thromboembolism and shock by Dr Nadeem (RMC)
 
Hemodynamic disorders
Hemodynamic disordersHemodynamic disorders
Hemodynamic disorders
 
IMMUNOPATHOLOGY
IMMUNOPATHOLOGYIMMUNOPATHOLOGY
IMMUNOPATHOLOGY
 
Hemodynamic disorders, thrombosis and shock (practical pathology)
Hemodynamic disorders, thrombosis and shock (practical pathology)Hemodynamic disorders, thrombosis and shock (practical pathology)
Hemodynamic disorders, thrombosis and shock (practical pathology)
 
Hemodynamic Disorders
Hemodynamic DisordersHemodynamic Disorders
Hemodynamic Disorders
 

Similar to Stat5 the t test

Chapter 4(1) Basic Logic
Chapter 4(1) Basic LogicChapter 4(1) Basic Logic
Chapter 4(1) Basic LogicSumit Prajapati
 
Chapter 4(1) Basic Logic
Chapter 4(1) Basic LogicChapter 4(1) Basic Logic
Chapter 4(1) Basic LogicSumit Prajapati
 
Chapter 4(1) Basic Logic
Chapter 4(1) Basic LogicChapter 4(1) Basic Logic
Chapter 4(1) Basic Logicghalan
 
slides Testing of hypothesis.pptx
slides Testing  of  hypothesis.pptxslides Testing  of  hypothesis.pptx
slides Testing of hypothesis.pptxssuser504dda
 
t-test and one way ANOVA.ppt game.ppt
t-test and one way ANOVA.ppt game.pptt-test and one way ANOVA.ppt game.ppt
t-test and one way ANOVA.ppt game.pptMohammedAbdela7
 
Unit # 04, chi-square test.ppt
Unit # 04, chi-square test.pptUnit # 04, chi-square test.ppt
Unit # 04, chi-square test.pptHarryPuri
 
Hypothesis Test _Two-sample t-test, Z-test, Proportion Z-test
Hypothesis Test _Two-sample t-test, Z-test, Proportion Z-testHypothesis Test _Two-sample t-test, Z-test, Proportion Z-test
Hypothesis Test _Two-sample t-test, Z-test, Proportion Z-testRavindra Nath Shukla
 
P G STAT 531 Lecture 7 t test and Paired t test
P G STAT 531 Lecture 7 t test and Paired t testP G STAT 531 Lecture 7 t test and Paired t test
P G STAT 531 Lecture 7 t test and Paired t testAashish Patel
 
1. The standard deviation of the diameter at breast height, or DBH.docx
1. The standard deviation of the diameter at breast height, or DBH.docx1. The standard deviation of the diameter at breast height, or DBH.docx
1. The standard deviation of the diameter at breast height, or DBH.docxpaynetawnya
 
Hypothesis testing for parametric data (1)
Hypothesis testing for parametric data (1)Hypothesis testing for parametric data (1)
Hypothesis testing for parametric data (1)KwambokaLeonidah
 
Hypothesis testing for parametric data
Hypothesis testing for parametric dataHypothesis testing for parametric data
Hypothesis testing for parametric dataKwambokaLeonidah
 
Non parametrics tests
Non parametrics testsNon parametrics tests
Non parametrics testsrodrick koome
 
inferentialstatistics-210411214248.pdf
inferentialstatistics-210411214248.pdfinferentialstatistics-210411214248.pdf
inferentialstatistics-210411214248.pdfChenPalaruan
 
This quiz consists of 20 questions most appear to be similar but now.docx
This quiz consists of 20 questions most appear to be similar but now.docxThis quiz consists of 20 questions most appear to be similar but now.docx
This quiz consists of 20 questions most appear to be similar but now.docxamit657720
 

Similar to Stat5 the t test (20)

Chapter 4(1) Basic Logic
Chapter 4(1) Basic LogicChapter 4(1) Basic Logic
Chapter 4(1) Basic Logic
 
Chapter 4(1) Basic Logic
Chapter 4(1) Basic LogicChapter 4(1) Basic Logic
Chapter 4(1) Basic Logic
 
Chapter 4(1) Basic Logic
Chapter 4(1) Basic LogicChapter 4(1) Basic Logic
Chapter 4(1) Basic Logic
 
Stat5 the t test
Stat5 the t testStat5 the t test
Stat5 the t test
 
Stat5 the t test
Stat5 the t testStat5 the t test
Stat5 the t test
 
slides Testing of hypothesis.pptx
slides Testing  of  hypothesis.pptxslides Testing  of  hypothesis.pptx
slides Testing of hypothesis.pptx
 
t-test and one way ANOVA.ppt game.ppt
t-test and one way ANOVA.ppt game.pptt-test and one way ANOVA.ppt game.ppt
t-test and one way ANOVA.ppt game.ppt
 
Unit # 04, chi-square test.ppt
Unit # 04, chi-square test.pptUnit # 04, chi-square test.ppt
Unit # 04, chi-square test.ppt
 
Parametric Test.pptx
Parametric Test.pptxParametric Test.pptx
Parametric Test.pptx
 
Hypothesis Test _Two-sample t-test, Z-test, Proportion Z-test
Hypothesis Test _Two-sample t-test, Z-test, Proportion Z-testHypothesis Test _Two-sample t-test, Z-test, Proportion Z-test
Hypothesis Test _Two-sample t-test, Z-test, Proportion Z-test
 
Stats chapter 13
Stats chapter 13Stats chapter 13
Stats chapter 13
 
P G STAT 531 Lecture 7 t test and Paired t test
P G STAT 531 Lecture 7 t test and Paired t testP G STAT 531 Lecture 7 t test and Paired t test
P G STAT 531 Lecture 7 t test and Paired t test
 
1. The standard deviation of the diameter at breast height, or DBH.docx
1. The standard deviation of the diameter at breast height, or DBH.docx1. The standard deviation of the diameter at breast height, or DBH.docx
1. The standard deviation of the diameter at breast height, or DBH.docx
 
Hypothesis testing for parametric data (1)
Hypothesis testing for parametric data (1)Hypothesis testing for parametric data (1)
Hypothesis testing for parametric data (1)
 
Hypothesis testing for parametric data
Hypothesis testing for parametric dataHypothesis testing for parametric data
Hypothesis testing for parametric data
 
Non parametrics tests
Non parametrics testsNon parametrics tests
Non parametrics tests
 
Medical statistics2
Medical statistics2Medical statistics2
Medical statistics2
 
inferentialstatistics-210411214248.pdf
inferentialstatistics-210411214248.pdfinferentialstatistics-210411214248.pdf
inferentialstatistics-210411214248.pdf
 
This quiz consists of 20 questions most appear to be similar but now.docx
This quiz consists of 20 questions most appear to be similar but now.docxThis quiz consists of 20 questions most appear to be similar but now.docx
This quiz consists of 20 questions most appear to be similar but now.docx
 
Inferential statistics
Inferential statisticsInferential statistics
Inferential statistics
 

More from Forensic Pathology (20)

Exercise 1 12 no solution
Exercise 1 12 no solutionExercise 1 12 no solution
Exercise 1 12 no solution
 
Analysis of variance
Analysis of varianceAnalysis of variance
Analysis of variance
 
Stat3 central tendency & dispersion
Stat3 central tendency & dispersionStat3 central tendency & dispersion
Stat3 central tendency & dispersion
 
Stat 4 the normal distribution & steps of testing hypothesis
Stat 4 the normal distribution & steps of testing hypothesisStat 4 the normal distribution & steps of testing hypothesis
Stat 4 the normal distribution & steps of testing hypothesis
 
Stat 2 data presentation2
Stat 2 data presentation2Stat 2 data presentation2
Stat 2 data presentation2
 
Correlation 3rd
Correlation 3rdCorrelation 3rd
Correlation 3rd
 
Stat 1 variables & sampling
Stat 1 variables & samplingStat 1 variables & sampling
Stat 1 variables & sampling
 
Pancreas 2
Pancreas 2Pancreas 2
Pancreas 2
 
Pancreas 1
Pancreas 1Pancreas 1
Pancreas 1
 
Liver 3
Liver 3Liver 3
Liver 3
 
Liver 2
Liver 2Liver 2
Liver 2
 
Liver 1
Liver 1Liver 1
Liver 1
 
The biliary tract
The biliary tractThe biliary tract
The biliary tract
 
Valvular heart diseases 4
Valvular heart diseases 4Valvular heart diseases 4
Valvular heart diseases 4
 
Pericardial dis.&cardiactumors 5
Pericardial dis.&cardiactumors 5Pericardial dis.&cardiactumors 5
Pericardial dis.&cardiactumors 5
 
Ischemic heart diseases 2
Ischemic heart diseases 2Ischemic heart diseases 2
Ischemic heart diseases 2
 
Hypertensive hd, and cardiomyopathy 3
Hypertensive hd, and cardiomyopathy 3Hypertensive hd, and cardiomyopathy 3
Hypertensive hd, and cardiomyopathy 3
 
Congenital heart diseases 1
Congenital heart diseases 1Congenital heart diseases 1
Congenital heart diseases 1
 
Arteriosclerosis 6
Arteriosclerosis 6Arteriosclerosis 6
Arteriosclerosis 6
 
Aneurysms & dissection 7
Aneurysms & dissection 7Aneurysms & dissection 7
Aneurysms & dissection 7
 

Recently uploaded

1029 - Danh muc Sach Giao Khoa 10 . pdf
1029 -  Danh muc Sach Giao Khoa 10 . pdf1029 -  Danh muc Sach Giao Khoa 10 . pdf
1029 - Danh muc Sach Giao Khoa 10 . pdfQucHHunhnh
 
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...christianmathematics
 
Paris 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activityParis 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activityGeoBlogs
 
Accessible design: Minimum effort, maximum impact
Accessible design: Minimum effort, maximum impactAccessible design: Minimum effort, maximum impact
Accessible design: Minimum effort, maximum impactdawncurless
 
Key note speaker Neum_Admir Softic_ENG.pdf
Key note speaker Neum_Admir Softic_ENG.pdfKey note speaker Neum_Admir Softic_ENG.pdf
Key note speaker Neum_Admir Softic_ENG.pdfAdmir Softic
 
Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...
Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...
Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...fonyou31
 
APM Welcome, APM North West Network Conference, Synergies Across Sectors
APM Welcome, APM North West Network Conference, Synergies Across SectorsAPM Welcome, APM North West Network Conference, Synergies Across Sectors
APM Welcome, APM North West Network Conference, Synergies Across SectorsAssociation for Project Management
 
A Critique of the Proposed National Education Policy Reform
A Critique of the Proposed National Education Policy ReformA Critique of the Proposed National Education Policy Reform
A Critique of the Proposed National Education Policy ReformChameera Dedduwage
 
Call Girls in Dwarka Mor Delhi Contact Us 9654467111
Call Girls in Dwarka Mor Delhi Contact Us 9654467111Call Girls in Dwarka Mor Delhi Contact Us 9654467111
Call Girls in Dwarka Mor Delhi Contact Us 9654467111Sapana Sha
 
The basics of sentences session 2pptx copy.pptx
The basics of sentences session 2pptx copy.pptxThe basics of sentences session 2pptx copy.pptx
The basics of sentences session 2pptx copy.pptxheathfieldcps1
 
Beyond the EU: DORA and NIS 2 Directive's Global Impact
Beyond the EU: DORA and NIS 2 Directive's Global ImpactBeyond the EU: DORA and NIS 2 Directive's Global Impact
Beyond the EU: DORA and NIS 2 Directive's Global ImpactPECB
 
1029-Danh muc Sach Giao Khoa khoi 6.pdf
1029-Danh muc Sach Giao Khoa khoi  6.pdf1029-Danh muc Sach Giao Khoa khoi  6.pdf
1029-Danh muc Sach Giao Khoa khoi 6.pdfQucHHunhnh
 
Holdier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdfHoldier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdfagholdier
 
Measures of Dispersion and Variability: Range, QD, AD and SD
Measures of Dispersion and Variability: Range, QD, AD and SDMeasures of Dispersion and Variability: Range, QD, AD and SD
Measures of Dispersion and Variability: Range, QD, AD and SDThiyagu K
 
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...EduSkills OECD
 
Q4-W6-Restating Informational Text Grade 3
Q4-W6-Restating Informational Text Grade 3Q4-W6-Restating Informational Text Grade 3
Q4-W6-Restating Informational Text Grade 3JemimahLaneBuaron
 
Activity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdfActivity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdfciinovamais
 

Recently uploaded (20)

Código Creativo y Arte de Software | Unidad 1
Código Creativo y Arte de Software | Unidad 1Código Creativo y Arte de Software | Unidad 1
Código Creativo y Arte de Software | Unidad 1
 
1029 - Danh muc Sach Giao Khoa 10 . pdf
1029 -  Danh muc Sach Giao Khoa 10 . pdf1029 -  Danh muc Sach Giao Khoa 10 . pdf
1029 - Danh muc Sach Giao Khoa 10 . pdf
 
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
 
Paris 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activityParis 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activity
 
Accessible design: Minimum effort, maximum impact
Accessible design: Minimum effort, maximum impactAccessible design: Minimum effort, maximum impact
Accessible design: Minimum effort, maximum impact
 
INDIA QUIZ 2024 RLAC DELHI UNIVERSITY.pptx
INDIA QUIZ 2024 RLAC DELHI UNIVERSITY.pptxINDIA QUIZ 2024 RLAC DELHI UNIVERSITY.pptx
INDIA QUIZ 2024 RLAC DELHI UNIVERSITY.pptx
 
Key note speaker Neum_Admir Softic_ENG.pdf
Key note speaker Neum_Admir Softic_ENG.pdfKey note speaker Neum_Admir Softic_ENG.pdf
Key note speaker Neum_Admir Softic_ENG.pdf
 
Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...
Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...
Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...
 
APM Welcome, APM North West Network Conference, Synergies Across Sectors
APM Welcome, APM North West Network Conference, Synergies Across SectorsAPM Welcome, APM North West Network Conference, Synergies Across Sectors
APM Welcome, APM North West Network Conference, Synergies Across Sectors
 
A Critique of the Proposed National Education Policy Reform
A Critique of the Proposed National Education Policy ReformA Critique of the Proposed National Education Policy Reform
A Critique of the Proposed National Education Policy Reform
 
Call Girls in Dwarka Mor Delhi Contact Us 9654467111
Call Girls in Dwarka Mor Delhi Contact Us 9654467111Call Girls in Dwarka Mor Delhi Contact Us 9654467111
Call Girls in Dwarka Mor Delhi Contact Us 9654467111
 
The basics of sentences session 2pptx copy.pptx
The basics of sentences session 2pptx copy.pptxThe basics of sentences session 2pptx copy.pptx
The basics of sentences session 2pptx copy.pptx
 
Beyond the EU: DORA and NIS 2 Directive's Global Impact
Beyond the EU: DORA and NIS 2 Directive's Global ImpactBeyond the EU: DORA and NIS 2 Directive's Global Impact
Beyond the EU: DORA and NIS 2 Directive's Global Impact
 
1029-Danh muc Sach Giao Khoa khoi 6.pdf
1029-Danh muc Sach Giao Khoa khoi  6.pdf1029-Danh muc Sach Giao Khoa khoi  6.pdf
1029-Danh muc Sach Giao Khoa khoi 6.pdf
 
Holdier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdfHoldier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdf
 
Measures of Dispersion and Variability: Range, QD, AD and SD
Measures of Dispersion and Variability: Range, QD, AD and SDMeasures of Dispersion and Variability: Range, QD, AD and SD
Measures of Dispersion and Variability: Range, QD, AD and SD
 
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
 
Mattingly "AI & Prompt Design: Structured Data, Assistants, & RAG"
Mattingly "AI & Prompt Design: Structured Data, Assistants, & RAG"Mattingly "AI & Prompt Design: Structured Data, Assistants, & RAG"
Mattingly "AI & Prompt Design: Structured Data, Assistants, & RAG"
 
Q4-W6-Restating Informational Text Grade 3
Q4-W6-Restating Informational Text Grade 3Q4-W6-Restating Informational Text Grade 3
Q4-W6-Restating Informational Text Grade 3
 
Activity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdfActivity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdf
 

Stat5 the t test

  • 2. 22 ApplicationsApplications  To compare the mean of a sample withTo compare the mean of a sample with population mean.population mean.  To compare the mean of one sampleTo compare the mean of one sample with the mean of another independentwith the mean of another independent sample.sample.  To compare between the valuesTo compare between the values (readings) of one sample but in 2(readings) of one sample but in 2 occasions.occasions.
  • 3. 33 1.Sample mean and population1.Sample mean and population meanmean  The general steps of testing hypothesis must beThe general steps of testing hypothesis must be followed.followed.  Ho: Sample mean=Population mean.Ho: Sample mean=Population mean.  Degrees of freedom = n - 1Degrees of freedom = n - 1 SE X t − − = µ
  • 4. 44 ExampleExample The following data represents hemoglobin values inThe following data represents hemoglobin values in gm/dl for 10 patients:gm/dl for 10 patients: Is the mean value for patients significantly differIs the mean value for patients significantly differ from the mean value of general populationfrom the mean value of general population (12 gm/dl) . Evaluate the role of chance.(12 gm/dl) . Evaluate the role of chance. 10.510.5 99 6.56.5 88 1111 77 7.57.5 8.58.5 9.59.5 1212
  • 5. 55 SolutionSolution  Mention all steps of testing hypothesis.Mention all steps of testing hypothesis. Then compare with tabulated value, for 9 df, and 5% level ofThen compare with tabulated value, for 9 df, and 5% level of significance. It is = 2.262significance. It is = 2.262 The calculated value>tabulated value.The calculated value>tabulated value. Reject Ho and conclude that there is a statistically significant differenceReject Ho and conclude that there is a statistically significant difference between the mean of sample and population mean, and thisbetween the mean of sample and population mean, and this difference is unlikely due to chance.difference is unlikely due to chance. 352.5 10 80201.1 1295.8 −= − =t
  • 6. 66
  • 7. 77 2.Two independent samples2.Two independent samples The following data represents weight in Kg for 10The following data represents weight in Kg for 10 males and 12 females.males and 12 females. Males:Males: Females:Females: 80 75 95 55 60 70 75 72 80 65 60 70 50 85 45 60 80 65 70 62 77 82
  • 8. 88 2.Two independent samples, cont.2.Two independent samples, cont.  Is there a statistically significant difference betweenIs there a statistically significant difference between the mean weight of males and females. Let alpha =the mean weight of males and females. Let alpha = 0.010.01  To solve it follow the steps and use this equation.To solve it follow the steps and use this equation. ) 11 ( 2 )1()1( 2121 2 22 2 11 21 nnnn SnSn XX t + −+ −+− − = − −
  • 9. 99 ResultsResults  Mean1=72.7 Mean2=67.17Mean1=72.7 Mean2=67.17  Variance1=128.46 Variance2=157.787Variance1=128.46 Variance2=157.787  Df = n1+n2-2=20Df = n1+n2-2=20  t = 1.074t = 1.074  The tabulated t, 2 sides, for alpha 0.01 is 2.845The tabulated t, 2 sides, for alpha 0.01 is 2.845  Then accept Ho and conclude that there is noThen accept Ho and conclude that there is no significant difference between the 2 means. Thissignificant difference between the 2 means. This difference may be due to chance.difference may be due to chance.  P>0.01P>0.01
  • 10. 1010 3.One sample in two occasions3.One sample in two occasions  Mention steps of testing hypothesis.Mention steps of testing hypothesis.  The df here = n – 1.The df here = n – 1. n sd d t − = 1 )( 2 2 − − = ∑ ∑ n n d d sd
  • 11. 1111 Example: Blood pressure of 8Example: Blood pressure of 8 patients, before & after treatmentpatients, before & after treatment BP beforeBP before BP afterBP after dd dd22 180180 140140 4040 16001600 200200 145145 5555 30253025 230230 150150 8080 64006400 240240 155155 8585 72257225 170170 120120 5050 25002500 190190 130130 6060 36003600 200200 140140 6060 36003600 165165 130130 3535 12251225 Mean d=465/8=58.125Mean d=465/8=58.125 ∑∑d=465d=465 ∑∑dd22 =29175=29175
  • 12. 1212 Results and conclusionResults and conclusion  t=9.387t=9.387  Tabulated t (df7), with level of significanceTabulated t (df7), with level of significance 0.05, two tails, = 2.360.05, two tails, = 2.36  We reject Ho and conclude that there isWe reject Ho and conclude that there is significant difference between BP readingssignificant difference between BP readings before and after treatment.before and after treatment.  P<0.05.P<0.05.