This document discusses using SPSS to conduct a chi-square test of independence. It provides an example of testing whether there is an association between area of residence (urban vs. rural) and BMI categories (normal weight vs. overweight/obese). The chi-square test involves stating hypotheses, calculating expected and observed frequencies, computing the test statistic in SPSS, and making a decision. No significant relationship was found between gender and BMI categories in another example exercise.
Chi-Square test for independence of attributes / Chi-Square test for checking association between two categorical variables, Chi-Square test for goodness of fit
Overviews non-parametric and parametric approaches to (bivariate) linear correlation. See also: http://en.wikiversity.org/wiki/Survey_research_and_design_in_psychology/Lectures/Correlation
Chi-Square test for independence of attributes / Chi-Square test for checking association between two categorical variables, Chi-Square test for goodness of fit
Overviews non-parametric and parametric approaches to (bivariate) linear correlation. See also: http://en.wikiversity.org/wiki/Survey_research_and_design_in_psychology/Lectures/Correlation
My attractive effective presentation is the proof of my hard work as i made it for those who can not take interest in their studies so as they can see this they will take interest too as well as for those who really want to do come thing different from others , they can use my presentation if any kind of help you want just mail me at ammara.aftab63@gmail.com
In Hypothesis testing parametric test is very important. in this ppt you can understand all types of parametric test with assumptions which covers Types of parametric, Z-test, T-test, ANOVA, F-test, Chi-Square test, Meaning of parametric, Fisher, one-sample z-test, Two-sample z-test, Analysis of Variance, two-way ANOVA.
Subscribe to Vision Academy for Video assistance
https://www.youtube.com/channel/UCjzpit_cXjdnzER_165mIiw
Explains how to select a statistical test suitable for your hypothesis. Suggests points to consider before deciding about a test. Gives a list of commonly used parametric and non-parametric tests with their purposes of use.
Measure of dispersion has two types Absolute measure and Graphical measure. There are other different types in there.
In this slide the discussed points are:
1. Dispersion & it's types
2. Definition
3. Use
4. Merits
5. Demerits
6. Formula & math
7. Graph and pictures
8. Real life application.
SPSS statistics - how to use SPSS for research, analysis, and surveys. Includes instructions and examples of how to: define a data file and variables, correlation analysis, multiple response sets, creating and editing charts, and much, much more!
My attractive effective presentation is the proof of my hard work as i made it for those who can not take interest in their studies so as they can see this they will take interest too as well as for those who really want to do come thing different from others , they can use my presentation if any kind of help you want just mail me at ammara.aftab63@gmail.com
In Hypothesis testing parametric test is very important. in this ppt you can understand all types of parametric test with assumptions which covers Types of parametric, Z-test, T-test, ANOVA, F-test, Chi-Square test, Meaning of parametric, Fisher, one-sample z-test, Two-sample z-test, Analysis of Variance, two-way ANOVA.
Subscribe to Vision Academy for Video assistance
https://www.youtube.com/channel/UCjzpit_cXjdnzER_165mIiw
Explains how to select a statistical test suitable for your hypothesis. Suggests points to consider before deciding about a test. Gives a list of commonly used parametric and non-parametric tests with their purposes of use.
Measure of dispersion has two types Absolute measure and Graphical measure. There are other different types in there.
In this slide the discussed points are:
1. Dispersion & it's types
2. Definition
3. Use
4. Merits
5. Demerits
6. Formula & math
7. Graph and pictures
8. Real life application.
SPSS statistics - how to use SPSS for research, analysis, and surveys. Includes instructions and examples of how to: define a data file and variables, correlation analysis, multiple response sets, creating and editing charts, and much, much more!
Aula de Métodos e Técnicas de Análise da Informação para Planejamento, julho de 2017, UFABC
Apresentação disponível em: https://youtu.be/cQ8ZfzL3SfI
Bases de dados disponíveis em:https://app.box.com/s/4yl70hj73c9mqyh1jb0l8skics4xf8i1
Poster for Society for Clinical Trials annual meeting in Boston, MA
Abstract
Randomization methods generally are designed to be both unpredictable and balanced between treatment allocations overall and within strata. However, when planning studies, little consideration is given to measuring these characteristics, nor are they examined jointly, and published comparisons between methods often use incompatible metrics and simulation assumptions. Furthermore, for purposes of real-world planning, such simulations often make unrealistic assumptions (e.g., equal sized strata), and summary statistics give limited information.
Affect of Metabolic Obesity and Body Mass Index in Coronary Artery DiseasesNikhil Gupta
The project aims to:
1) Train a model capable of predicting the GENSINI score which determines the severity of CAD in the following groups-
-Metabolically Healthy Normal Weight (MHNW)
-Metabolically Obese Normal Weight (MONW)
-Metabolically Healthy Obese (MHO)
-Metabolically Abnormal Obese (MAO)
2) Find the group showing a good association to severity of CAD that is which category is more prone to CAD, metabolically obese or phenotypically obese.
3) Find the prognostic markers for CAD among factors like HBA1C, FI, HOMA IR , TC, TG, HDL, LDL and hsCRP and which group shows more association?
The data was collected by Kasturba Medical College, Manipal.
The results obtained were presented at Hackabout 2016, a data analysis challenge, organized by Philips in Manipal University. We were among the best 5 teams.
A presentation I have presented as a part of the Saudi Board of Community Medicine, Western Region. It simplifies the ideas behind hypothesis and hypothesis testing, also contains many different approaches of choosing the best statistical tests needed in any study.
This quiz consists of 20 questions most appear to be similar but now.docxamit657720
This quiz consists of 20 questions most appear to be similar but now really. I ned someone who is familiar with bio-statistics and math. The due date is tomorrow 4 pm PST. or (16:00). Please if you accept handshake you must do the work not get from previous papers or tell me you had emergency an hour before its due. This is important to me.
attached is the file just in case you need it in word format. Thank you in advance.
1.
The standard deviation of the diameter at breast height, or DBH, of the slash pine tree is less than one inch. Identify the Type I error. (Points : 1)
[removed] Fail to support the claim σ < 1 when σ < 1 is true.
[removed] Support the claim μ < 1 when μ = 1 is true.
[removed]
Support the claim σ < 1 when σ = 1 is true.
[removed] Fail to support the claim μ < 1 when μ < 1 is true.
1a. The EPA claims that fluoride in children's drinking water should be at a mean level of less than 1.2 ppm, or parts per million, to reduce the number of dental cavities. Identify the Type I error. (Points : 1)
[removed] Fail to support the claim σ < 1.2 when σ < 1.2 is true.
[removed] Support the claim μ < 1.2 when μ = 1.2 is true.
[removed] Support the claim σ < 1.2 when σ = 1.2 is true.
[removed] Fail to support the claim μ < 1.2 when μ < 1.2 is true.
2.
Biologists are investigating if their efforts to prevent erosion on the bank of a stream have been statistically significant. For this stream, a narrow channel width is a good indicator that erosion is not occurring. Test the claim that the mean width of ten locations within the stream is greater than 3.7 meters. Assume that a simple random sample has been taken, the population standard deviation is not known, and the population is normally distributed. Use the following sample data:
3.3 3.3 3.5 4.9 3.5 4.1 4.1 5 7.3 6.2
What is the P-value associated with your test statistic? Report your answer with three decimals, e.g., .987 (Points : 1)
2a. Medical researchers studying two therapies for treating patients infected with Hepatitis C found the following data. Assume a .05 significance level for testing the claim that the proportions are not equal. Also, assume the two simple random samples are independent and that the conditions np ≥ 5 and nq ≥ 5 are satisfied.
Therapy 1
Therapy 2
Number of patients
39
47
Eliminated Hepatitis
20
13
C infection
Construct a 95% confidence interval estimate of the odds ratio of the odds for having Hepatitis C after Therapy 1 to the odds for having Hepatitis C after Therapy 2. Give your answer with two decimals, e.g., (12.34,56.78) (Points : 0.5)
[removed]
3. Researchers studying sleep loss followed the length of sleep, in hours, of 10 individuals with insomnia before and after cognitive behavioral therapy (CBT). Assume a .05 significance level to test the claim that there is a difference between the length of sleep of individuals before and after CBT. Also, assume the data consist of matched pair ...
Evaluating a Propensity Score Adjustment for Combining Probability and Non-Pr...ICF
Research designs that make use of non-probability samples offer the possibility of fit-for-purpose data at a fraction of the cost of probability-based designs. In 2012, ICF International designed and fielded a national survey in Canada that gathered data about Canadians’ 2011 nature-based recreation, subsistence, and conservation activities.
To support larger sample sizes at the provincial level, a hybrid design was employed that combined a stratified national probability sample of more than 76,000 adults randomly selected from an addressed-based sample (ABS) with a non-probability sample of adults randomly recruited from a purchased Web panel. As part of the survey weighting, ICF developed a propensity score adjustment to combine the data from the probability and non-probability samples.
This presentation will evaluate the effectiveness of the propensity score adjustment in decreasing bias in key demographic and survey outcomes in the non-probability sample. We will also discuss implications concerning the effectiveness of hybrid designs and the degree to which non-probability data could be considered fit-for-purpose in similar survey applications.
To learn more visit: www.icfi.com/SurveyResearch
4. Performed statistical analysis on a chosen data table and understood relationship amongst different data fields using IBM SPSS software.
Methodologies: Multi linear regression, Logistic linear regression
IBM SPSS
Pulmonary Thromboembolism - etilogy, types, medical- Surgical and nursing man...VarunMahajani
Disruption of blood supply to lung alveoli due to blockage of one or more pulmonary blood vessels is called as Pulmonary thromboembolism. In this presentation we will discuss its causes, types and its management in depth.
These lecture slides, by Dr Sidra Arshad, offer a quick overview of physiological basis of a normal electrocardiogram.
Learning objectives:
1. Define an electrocardiogram (ECG) and electrocardiography
2. Describe how dipoles generated by the heart produce the waveforms of the ECG
3. Describe the components of a normal electrocardiogram of a typical bipolar leads (limb II)
4. Differentiate between intervals and segments
5. Enlist some common indications for obtaining an ECG
Study Resources:
1. Chapter 11, Guyton and Hall Textbook of Medical Physiology, 14th edition
2. Chapter 9, Human Physiology - From Cells to Systems, Lauralee Sherwood, 9th edition
3. Chapter 29, Ganong’s Review of Medical Physiology, 26th edition
4. Electrocardiogram, StatPearls - https://www.ncbi.nlm.nih.gov/books/NBK549803/
5. ECG in Medical Practice by ABM Abdullah, 4th edition
6. ECG Basics, http://www.nataliescasebook.com/tag/e-c-g-basics
Report Back from SGO 2024: What’s the Latest in Cervical Cancer?bkling
Are you curious about what’s new in cervical cancer research or unsure what the findings mean? Join Dr. Emily Ko, a gynecologic oncologist at Penn Medicine, to learn about the latest updates from the Society of Gynecologic Oncology (SGO) 2024 Annual Meeting on Women’s Cancer. Dr. Ko will discuss what the research presented at the conference means for you and answer your questions about the new developments.
Prix Galien International 2024 Forum ProgramLevi Shapiro
June 20, 2024, Prix Galien International and Jerusalem Ethics Forum in ROME. Detailed agenda including panels:
- ADVANCES IN CARDIOLOGY: A NEW PARADIGM IS COMING
- WOMEN’S HEALTH: FERTILITY PRESERVATION
- WHAT’S NEW IN THE TREATMENT OF INFECTIOUS,
ONCOLOGICAL AND INFLAMMATORY SKIN DISEASES?
- ARTIFICIAL INTELLIGENCE AND ETHICS
- GENE THERAPY
- BEYOND BORDERS: GLOBAL INITIATIVES FOR DEMOCRATIZING LIFE SCIENCE TECHNOLOGIES AND PROMOTING ACCESS TO HEALTHCARE
- ETHICAL CHALLENGES IN LIFE SCIENCES
- Prix Galien International Awards Ceremony
Tom Selleck Health: A Comprehensive Look at the Iconic Actor’s Wellness Journeygreendigital
Tom Selleck, an enduring figure in Hollywood. has captivated audiences for decades with his rugged charm, iconic moustache. and memorable roles in television and film. From his breakout role as Thomas Magnum in Magnum P.I. to his current portrayal of Frank Reagan in Blue Bloods. Selleck's career has spanned over 50 years. But beyond his professional achievements. fans have often been curious about Tom Selleck Health. especially as he has aged in the public eye.
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Introduction
Many have been interested in Tom Selleck health. not only because of his enduring presence on screen but also because of the challenges. and lifestyle choices he has faced and made over the years. This article delves into the various aspects of Tom Selleck health. exploring his fitness regimen, diet, mental health. and the challenges he has encountered as he ages. We'll look at how he maintains his well-being. the health issues he has faced, and his approach to ageing .
Early Life and Career
Childhood and Athletic Beginnings
Tom Selleck was born on January 29, 1945, in Detroit, Michigan, and grew up in Sherman Oaks, California. From an early age, he was involved in sports, particularly basketball. which played a significant role in his physical development. His athletic pursuits continued into college. where he attended the University of Southern California (USC) on a basketball scholarship. This early involvement in sports laid a strong foundation for his physical health and disciplined lifestyle.
Transition to Acting
Selleck's transition from an athlete to an actor came with its physical demands. His first significant role in "Magnum P.I." required him to perform various stunts and maintain a fit appearance. This role, which he played from 1980 to 1988. necessitated a rigorous fitness routine to meet the show's demands. setting the stage for his long-term commitment to health and wellness.
Fitness Regimen
Workout Routine
Tom Selleck health and fitness regimen has evolved. adapting to his changing roles and age. During his "Magnum, P.I." days. Selleck's workouts were intense and focused on building and maintaining muscle mass. His routine included weightlifting, cardiovascular exercises. and specific training for the stunts he performed on the show.
Selleck adjusted his fitness routine as he aged to suit his body's needs. Today, his workouts focus on maintaining flexibility, strength, and cardiovascular health. He incorporates low-impact exercises such as swimming, walking, and light weightlifting. This balanced approach helps him stay fit without putting undue strain on his joints and muscles.
Importance of Flexibility and Mobility
In recent years, Selleck has emphasized the importance of flexibility and mobility in his fitness regimen. Understanding the natural decline in muscle mass and joint flexibility with age. he includes stretching and yoga in his routine. These practices help prevent injuries, improve posture, and maintain mobilit
Flu Vaccine Alert in Bangalore Karnatakaaddon Scans
As flu season approaches, health officials in Bangalore, Karnataka, are urging residents to get their flu vaccinations. The seasonal flu, while common, can lead to severe health complications, particularly for vulnerable populations such as young children, the elderly, and those with underlying health conditions.
Dr. Vidisha Kumari, a leading epidemiologist in Bangalore, emphasizes the importance of getting vaccinated. "The flu vaccine is our best defense against the influenza virus. It not only protects individuals but also helps prevent the spread of the virus in our communities," he says.
This year, the flu season is expected to coincide with a potential increase in other respiratory illnesses. The Karnataka Health Department has launched an awareness campaign highlighting the significance of flu vaccinations. They have set up multiple vaccination centers across Bangalore, making it convenient for residents to receive their shots.
To encourage widespread vaccination, the government is also collaborating with local schools, workplaces, and community centers to facilitate vaccination drives. Special attention is being given to ensuring that the vaccine is accessible to all, including marginalized communities who may have limited access to healthcare.
Residents are reminded that the flu vaccine is safe and effective. Common side effects are mild and may include soreness at the injection site, mild fever, or muscle aches. These side effects are generally short-lived and far less severe than the flu itself.
Healthcare providers are also stressing the importance of continuing COVID-19 precautions. Wearing masks, practicing good hand hygiene, and maintaining social distancing are still crucial, especially in crowded places.
Protect yourself and your loved ones by getting vaccinated. Together, we can help keep Bangalore healthy and safe this flu season. For more information on vaccination centers and schedules, residents can visit the Karnataka Health Department’s official website or follow their social media pages.
Stay informed, stay safe, and get your flu shot today!
Explore natural remedies for syphilis treatment in Singapore. Discover alternative therapies, herbal remedies, and lifestyle changes that may complement conventional treatments. Learn about holistic approaches to managing syphilis symptoms and supporting overall health.
The prostate is an exocrine gland of the male mammalian reproductive system
It is a walnut-sized gland that forms part of the male reproductive system and is located in front of the rectum and just below the urinary bladder
Function is to store and secrete a clear, slightly alkaline fluid that constitutes 10-30% of the volume of the seminal fluid that along with the spermatozoa, constitutes semen
A healthy human prostate measures (4cm-vertical, by 3cm-horizontal, 2cm ant-post ).
It surrounds the urethra just below the urinary bladder. It has anterior, median, posterior and two lateral lobes
It’s work is regulated by androgens which are responsible for male sex characteristics
Generalised disease of the prostate due to hormonal derangement which leads to non malignant enlargement of the gland (increase in the number of epithelial cells and stromal tissue)to cause compression of the urethra leading to symptoms (LUTS
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Ethanol (CH3CH2OH), or beverage alcohol, is a two-carbon alcohol
that is rapidly distributed in the body and brain. Ethanol alters many
neurochemical systems and has rewarding and addictive properties. It
is the oldest recreational drug and likely contributes to more morbidity,
mortality, and public health costs than all illicit drugs combined. The
5th edition of the Diagnostic and Statistical Manual of Mental Disorders
(DSM-5) integrates alcohol abuse and alcohol dependence into a single
disorder called alcohol use disorder (AUD), with mild, moderate,
and severe subclassifications (American Psychiatric Association, 2013).
In the DSM-5, all types of substance abuse and dependence have been
combined into a single substance use disorder (SUD) on a continuum
from mild to severe. A diagnosis of AUD requires that at least two of
the 11 DSM-5 behaviors be present within a 12-month period (mild
AUD: 2–3 criteria; moderate AUD: 4–5 criteria; severe AUD: 6–11 criteria).
The four main behavioral effects of AUD are impaired control over
drinking, negative social consequences, risky use, and altered physiological
effects (tolerance, withdrawal). This chapter presents an overview
of the prevalence and harmful consequences of AUD in the U.S.,
the systemic nature of the disease, neurocircuitry and stages of AUD,
comorbidities, fetal alcohol spectrum disorders, genetic risk factors, and
pharmacotherapies for AUD.
New Directions in Targeted Therapeutic Approaches for Older Adults With Mantl...i3 Health
i3 Health is pleased to make the speaker slides from this activity available for use as a non-accredited self-study or teaching resource.
This slide deck presented by Dr. Kami Maddocks, Professor-Clinical in the Division of Hematology and
Associate Division Director for Ambulatory Operations
The Ohio State University Comprehensive Cancer Center, will provide insight into new directions in targeted therapeutic approaches for older adults with mantle cell lymphoma.
STATEMENT OF NEED
Mantle cell lymphoma (MCL) is a rare, aggressive B-cell non-Hodgkin lymphoma (NHL) accounting for 5% to 7% of all lymphomas. Its prognosis ranges from indolent disease that does not require treatment for years to very aggressive disease, which is associated with poor survival (Silkenstedt et al, 2021). Typically, MCL is diagnosed at advanced stage and in older patients who cannot tolerate intensive therapy (NCCN, 2022). Although recent advances have slightly increased remission rates, recurrence and relapse remain very common, leading to a median overall survival between 3 and 6 years (LLS, 2021). Though there are several effective options, progress is still needed towards establishing an accepted frontline approach for MCL (Castellino et al, 2022). Treatment selection and management of MCL are complicated by the heterogeneity of prognosis, advanced age and comorbidities of patients, and lack of an established standard approach for treatment, making it vital that clinicians be familiar with the latest research and advances in this area. In this activity chaired by Michael Wang, MD, Professor in the Department of Lymphoma & Myeloma at MD Anderson Cancer Center, expert faculty will discuss prognostic factors informing treatment, the promising results of recent trials in new therapeutic approaches, and the implications of treatment resistance in therapeutic selection for MCL.
Target Audience
Hematology/oncology fellows, attending faculty, and other health care professionals involved in the treatment of patients with mantle cell lymphoma (MCL).
Learning Objectives
1.) Identify clinical and biological prognostic factors that can guide treatment decision making for older adults with MCL
2.) Evaluate emerging data on targeted therapeutic approaches for treatment-naive and relapsed/refractory MCL and their applicability to older adults
3.) Assess mechanisms of resistance to targeted therapies for MCL and their implications for treatment selection
These simplified slides by Dr. Sidra Arshad present an overview of the non-respiratory functions of the respiratory tract.
Learning objectives:
1. Enlist the non-respiratory functions of the respiratory tract
2. Briefly explain how these functions are carried out
3. Discuss the significance of dead space
4. Differentiate between minute ventilation and alveolar ventilation
5. Describe the cough and sneeze reflexes
Study Resources:
1. Chapter 39, Guyton and Hall Textbook of Medical Physiology, 14th edition
2. Chapter 34, Ganong’s Review of Medical Physiology, 26th edition
3. Chapter 17, Human Physiology by Lauralee Sherwood, 9th edition
4. Non-respiratory functions of the lungs https://academic.oup.com/bjaed/article/13/3/98/278874
1. Using SPSS for Chi Square
Dr Athar Khan
MBBS, MCPS, DPH, DCPS-HCSM, DCPS-HPE, MBA,
PGD-Statistics
Associate Professor
Liaquat College of Medicine & Dentistry
3. Introduction
• The chi-square test for independence, also
called Pearson's chi-square test or the chi-
square test of association, is used to
discover if there is a relationship between
two categorical variables.
12/7/2016 3DR ATHAR KHAN - LCMD
4. BMI
• Body mass index (BMI) is a measure of body fat
based on height and weight that applies to both
adult men and women.
– Under & normal weight: BMI <25
– Overweight & obesity: BMI ≥ 25
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5. Question 1
• Is there any association between living in
a suburban area and being overweight?
– Under & normal weight: BMI <25
– Overweight & obese: BMI ≥ 25
Chi Square test
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6. Dataset
• 30 adults aged 18+ (males and females) were recruited to
study the difference in BMI according to their area of
residence.
• Variables
– Sex (female=1, male=0)
– BMI
– Urban or rural (urban=0, rural=1)
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7. Area of Residence
Total
Urban Rural
BMI Categories
Normal and
Underweight 7 11 18
Overweight and
Obesity 10 2 12
Total 17 13 30
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8. Assumptions
• Assumption #1:
• Two variables should be measured at
an ordinal or nominal
level (i.e., categorical data).
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9. Assumptions
• Assumption #2:
• Two variable should consist of two or more
categorical, independent groups. Example
independent variables that meet this criterion
include gender (2 groups: Males and Females),
ethnicity (e.g., 3 groups: Caucasian, African
American and Hispanic), physical activity level
(e.g., 4 groups: sedentary, low, moderate and
high), profession (e.g., 5 groups: surgeon, doctor,
nurse, dentist, therapist), and so forth.
12/7/2016 9DR ATHAR KHAN - LCMD
10. Hypothesis Testing– Step by Step
• Step 1: Stating the null hypothesis
– H0: Area of residence and BMI categories are
independent
– Ha: Area of residence and BMI categories are
dependent
OR
– H0: There is no association between living in an
urban area and being overweight
– Ha: There is an association between Living in an
urban area and being overweight are dependent
• Step 2: Significance level
– Alpha = 0.05
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11. Hypothesis Testing– Step by Step
• Step 3: Critical value
– Sampling distribution = χ2 distribution
– Df = (r-1)(c-1) = 1 (a 2-by-2 table)
– χ2 (critical) = 3.481
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12. Hypothesis Testing– Step by Step
• Step 4: Calculated Value
– 1. Draw a contingency table.
– 2. Enter the Observed frequencies or counts (O)
– 3. Calculate totals (in the margins).
Area of Residence
Total
Urban Rural
BMI Categories
Normal and
Underweight 7 11 18
Overweight and
Obesity 10 2 12
Total 17 13 30
12/7/2016 12DR ATHAR KHAN - LCMD
13. Hypothesis Testing– Step by Step
• Step 4: Calculated Value
• 4.Calculate the Expected frequencies (E) a. For each cell: Column total x
Row total/N b. Write the Expected frequency into the appropriate box
in the table.
• CHECK: Expected frequencies (E) marginal totals are the same as for
Observed frequencies (O)Eyeball the contingency table, noting where
the differences between O (observed) and E (Expected) values occur. If
they are close to each other, the levels of the independent (predictor) variable are
not having an effect.
Area of Residence
Total
Urban Rural
BMI Categories
Normal and
Underweight 7 11 18
Overweight and
Obesity 10 2 12
Total 17 13 30
10.2 7.8
6.8 5.2
12/7/2016 13DR ATHAR KHAN - LCMD
14. Important Point:
Chi-square can be used if no more than 20% of
the expected frequencies are less than 5 and none
is less than 1 (see note 'a.' at the bottom of SPSS
output to see if this is a problem).
It is possible to 'pool' or 'collapse' categories into
fewer, but this must only be done if it is meaningful
to group the data in this way.
12/7/2016 14DR ATHAR KHAN - LCMD
15. Hypothesis Testing– Step by Step
Area of Residence
Total
Urban Rural
BMI Categories
Normal and
Underweight 7 11 18
Overweight and
Obesity 10 2 12
Total 17 13 30
10.2 7.8
6.8 5.2
12/7/2016 15DR ATHAR KHAN - LCMD
18. Hypothesis Testing– Step by Step
Step 4: computing the test statistic in SPSS
12/7/2016 18DR ATHAR KHAN - LCMD
19. Hypothesis Testing– Step by Step
• Step 5: making a decision and interpreting the
results of the test
overweight_1 * urban Crosstabulation
329 468 797
385.7 411.3 797.0
155 48 203
98.3 104.7 203.0
484 516 1000
484.0 516.0 1000.0
Count
Expected Count
Count
Expected Count
Count
Expected Count
0
1
overweight_1
Total
0 1
urban
Total
Chi-Square Tests
79.699b 1 .000
78.301 1 .000
82.696 1 .000
.000 .000
79.619 1 .000
1000
Pearson Chi-Square
Continuity Correctiona
Likelihood Ratio
Fisher's Exact Test
Linear-by-Linear
Association
N of Valid Cases
Value df
Asymp. Sig.
(2-sided)
Exact Sig.
(2-sided)
Exact Sig.
(1-sided)
Computed onlyfor a 2x2 tablea.
0 cells (.0%) have expected count less than 5. The minimum expected count is 98.
25.
b.
Result
(χ2 obtained)12/7/2016 19DR ATHAR KHAN - LCMD
20. Exercise
• Does a significant relationship exist between
Gender and BMI categories ?
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22. Chi-Square Tests
Value df
Asymp. Sig.
(2-sided)
Exact Sig. (2-
sided)
Exact Sig.
(1-sided)
Pearson Chi-Square .023a 1 .879
Continuity Correctionb
.000 1 1.000
Likelihood Ratio .023 1 .879
Fisher's Exact Test 1.000 .588
Linear-by-Linear
Association .022 1 .881
N of Valid Cases 30
a. 1 cells (25.0%) have expected count less than 5. The minimum expected count is
4.80.
b. Computed only for a 2x2 table
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