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ROLE OF BIOSTATISTICS IN PHYSIOTHERAPY

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Vishal Jevtani

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Transcript of ROLE OF BIOSTATISTICS IN PHYSIOTHERAPY

What is Statistics?
The tools of statistics are employed in many fields like business, education, psychology, agriculture, economics etc.
When the data analyzed are derived from the biological science we use the term biostatistics .


Founder of Statistics
BIOSTATISTICS
The Study of analyzing , collecting and distributing data which is applicable in field of medical science is known as biostatistics.

Statistics
Collecting Data
e.g., Sample, Survey, Observe, Simulate
Characterizing Data
e.g., Organize/Classify, Count, Summarize
Presenting Data
e.g., Tables, Charts, Statements
Interpreting Results
e.g. Infer, Conclude, Specify Confidence

ROLE OF BIOSTATISTICS IN PHYSIOTHERAPY
ROLE OF BIOSTATISTICS IN PHYSIOTHERAPY
Anjani Advani
Ehtesham Ullah Khan
Pooja Vasandani
Farheen Abdul Kalam
Syed Osama
Kajal Kumari
Wasey Ali
Simran Chandwani
Anum Kumari
Team Members
Father of Statistics

Sir Ronald A. Fisher

Role of Bio-Statistics
Protocol Development
Management
Study Implementation
Study Monitoring
Data Analysis
Report/Manuscript Writing

BIOSTATISTICS
The Study of analyzing , collecting and distributing data which is applicable in field of medical science is known as biostatistics.

For Example
If you want to find the average availability of medicine in a group of patients in ward than simply add up all the patients in ward and divided by the number of patients.


The systematic investigation into and study of materials and sources in order to establish facts and reach new conclusions.
A process of steps used to collect and analyze information to increase our understanding of a topic or issue.
It consists of three steps:
Pose a question.
Collect data to answer the question , present an answer to the question.
Basically research is based on hypothesis

MEDIAN
The median is the middle value of a set of Data
The median is used in a variety of Statistics.
Too calculate median , the numbers in a set of data are arranged in ascending or descending order .

MODE
The mode is the most frequent observed value in a Data.
FOR EXAMPLE:
If you’d like to know the most popular new born baby boy name in hospital for 2008 year records you may go to the hospital website and find out that Jacob was the most popular.


Use of Biostatistics In Medical Sector
Documentation of medical history of diseases.
Planning and conduct of clinical studies.
Evaluating the merits of different procedures.
In providing methods for definition of “normal” and “abnormal”.
To provide the magnitude of any health problem in the community.
To find out the basic factors underlying the illhealth.
To evaluate the health programs which was introduced in the community (success/failure).
To introduce and promote health legislation.

Kind Of Statistics
Descriptive Statistics
Inferential Statistics

Descriptive Statistics
Organize and summarize data
OR
A way to summarize data from a sample or a population
Distributed Statistic include the frequency distribution & its interpretation like mean mode and measure of dispersion.

Methods of presentation of data
Numerical presentation
Graphical presentation
Mathematical presentation

Numerical Presentation
Types Of Data
Graphical Representation
Quantitative
Line graph
Histogram
Scatter plot

Qualitative
Pie Chart
Bar Graph

Quantitative Charts
Line Graph
Histogram
Scatter Plot
Pie Chart
Bar Chart
Doughnut
Mathematical presentation
3-Mathematical presentation
Measures of location :
Measures of central tendency
Frequency distribution
Measures of non central locations (Quartiles, Percentiles )
Measures of dispersion

Measures of Central Tendency
The average, equal to the sum of the observations
divided by the number of observations
Arithmetic mean (mean) (Σ(x)/N)
Sum of all observations
Number of observations

Mean:

Measures of Central Tendency
The value which occurs with the greatest frequency i.e. the most common value. or
The value that occurs most often, there can be more than one—”multimodal” data.

Mode:

Measures of Central Tendency

Median the observation which lies in the middle of the ordered observation
Or
The value that divides the frequency distribution in half.

Midrange = Smallest observation + Largest observation
2

Median:

Frequency Distribution
Description of data, versus theoretical distribution ( Normal Distribution – Mean and a variance )
The Formulas for frequencies of distribution from ungroup into group data are not accurately applicable when the no. of observations are too small or too large.

Which to Use?
Measures Of Distribution
Group of analytical tools that describes the spread or variability of a data set

Measures of dispersion OR VARIABILITY
Range
Variance
Coefficient of variation
Standard deviation
Standard error
Quartile
Semi-interquartile range

Range

For any set of data, the range of the set is given by
Range = (greatest value in set) – (least value in set).

EXAMPLE:
The normal value of RBcs in human is 3000-11000 McL so the range of WBcs in human is 7000 McL which is standard by diagnosis.

Standard Deviation & Variance


The positive not of square deviation is known as STANDARD DEVIATION.
Symbol: σ (sigma)
FORMULA:

The square root of standard deviation known as VARIANCE.
Symbol: σ ²
FORMULA:

Find the standard deviation and variance of the weight (in lbs) of NEW BORN babies in a hospital is 1, 2, 8, 11, 13.

Standard deviation is 4.77
Variance is 22.8

PROBABILITY


JOINT PROBABILITY
Occurrence of two events simultaneously.
EXAMPLE
A component of Physiotherapy that is suspension therapy through tis a neurological impaired patient can get joint stability and relaxation

POSTERIOR PROBABILITY
Once study is carried out, the data is collected and the probability is modified in the light of result.

EXAMPLE

Health department has reported that 84 deaths ,16 from cancer and from heart failure. The probability of death is 60% the health department use posterior probability.

MUTUALLY EXCLUSIVE EVENT
Event that can not happen together

EXAMPLE
One person sick will not healthy simultaneously.

Sampling

Selecting observation provide adequate description to population

Systemic Sampling
Sample arrange in order
Systemic sampling is a statistical method involving the selection if elements from an ordered sampling frame.

Snowball Sampling
Inferential Statistics
Useful for finding subject who may not be dealing to close. Is a non probability sampling that is appropriate to use in research when the members of a population are difficult to locate.





Methods used to make inferences about the relationship between the dependent and independent variables in a population, based on a sample of observations from that population
OR
Used to make an inference, on the basis of data, about the (non)existence of a relationship between the independent and dependent variable

Hypothesis is an Intelligent or educated Guess
Hypothesis testing involves determining if differences in dependent variable measures are due to sampling error, or to a real relationship between independent and dependent measures.

Three basic steps: –
Define the hypothesis
Select appropriate statistical test
Decide whether to accept or reject the hypothesis

Hypothesis
SAMPLING It is the process to draw the sample from population

POPULATION A set of object element or people who have similar of characteristics to represent set its identity

SAMPLE A small part of relevant population which is use to analyze through the process of sampling and hypothesis and characteristics of that sample represent the population

TYPES OF HYPOTHESIS

NULL HYPOTHESIS
The hypothesis which we want to test.
Denoted by Ho.
Exercise: Physical exercise does not increase mood.
ALTERNATIVE HYPOTHESIS
The opposite to the null hypothesis.
Denothypothesised by Ha.

Example: Physical exercise increase mood.

Accepting or Rejecting the Null Hypothesis
The region of unlikely values is the level of significance Alpha (type I error) or Beta (type II error)

Alpha (type I error) : When the null hypothesis is originally true and we reject it
Beta (type II error) : When the null hypothesis is originally false and we accept it ( Power of Study )

A researcher thinks that if knee surgery patients go to physical therapy twice a week (instead of 3 times), their recovery period will be longer. Average recovery times for knee surgery patients is 8.2 weeks. 

STATISTICAL TEST
The decision to reject the null hypothesis based on statistics called test statistics.

CRITICAL VALUE
It is used to separate the sample size into two regions.

EXAMPLE
 A type II error would occur if we accepted that the drug had no effect on a diseases.


A drug being used to treat a disease. If we reject the null hypothesis in this situation, then our claim is that the drug does in fact have some effect on a disease. But if the null hypothesis is true, then in reality the drug does not combat the disease at all. The drug is falsely claimed to have a positive effect on a disease.

Test of significance that makes assumption s about the parameters of population distribution(s)from which ones data are drawn.

Types of parametric test:

Chi square test
T test
Z test
Anova test

Chi square test

Test of significance used to check the association of two variables b/w contingency table.
Chi-square tests enable us to compare observed and expected frequencies objectively

The Formula for calculating chi-square (χ²) is:  

Types of Chi Square Test:

Row X column chi square test
Fisher Exact chi square test
McNamara chi square test
Maental Haezal chi square test
Chi square test for trends
Test of homogeneity.

A study was conducted among the population of 5000 out of which 2000 were smokers and 3000 were non smokers .Among smokers 84 had develop lungs cancer while on the other hand 87 among non smokers had develop lungs cancer. To check the association b/w smokers & lungs cancer.

T-Test or Student TEST:

Test of significance used to compare the sample mean with the population mean to check weather the observed value is differentiate or not.
In T-Test or Student the sample size must be less than 30.
FORMULA:

Two sample T-Test:

A test used to compare two population means based on independent samples from two populations or groups.

The following example that the mean values obtained in a laboratory test comparing hip and lower back flexion of randomly taken males and females. The following measurements in centimeters were obtained by using specific test.

For Example:

Paired T-Test:

A significant test used to compare two variables on same individuals.
Sample size should be less than 30.
For example:
A group of 19 people who suffered from frozen shoulder , initially this group was treated with muscle energy technique for a month.MMT readings that came before and after treatment are:


The Process
Use Of Statistical Techniques in Physical Therapy
10 most common statistical techniques used in Physical Therapy are as follows
Descriptive statistics
One-way analysis of variance (ANOVA)
t test, factorial ANOVA,
infraclass correlation
appropriate post hoc analyses
Pearson correlation
Regression
Chi square
nonparametric tests analogous to the t test

Areas Of Physical Therapy
Areas Of Physical Therapy
Physiotherapy contributes to the health and well-being of people in a variety of ways in a range of different settings such as in hospital, GP surgeries, at home or in private practice. Others may be employed in the workplace, in schools, sports clubs and leisure centers or care homes.

Working with people of all ages to increase activity levels, improving general health and addressing related conditions such as obesity
Preventing people incurring injury in work and helping them to return to work after a period of incapacity, for example as the result of a musculoskeletal disorder like back pain

Providing rehabilitation services to help people recover from a heart attack or a stroke
Supporting children with developmental movement problems or learning difficulties
Supporting people with long-term conditions, such as Chronic Obstructive Pulmonary Disease (COPD) or diabetes, to manage their condition and maintain their independence


Treating elderly patients with arthritis or helping them to recover from a fall and prevent it happening again, supporting them to maintain mobility and independence
Contributing to the health and well-being of people with mental health problems
Working as part of palliative care teams to help patients and their carers manage the condition, including pain relief.


Preventing and treating sports injuries - from elite sportsmen and women, such as footballers or Olympic athletes, to those of us who injure ourselves in leisure activities such as gardening
Supporting women with ante- and post-natal care, exercise and posture and rehabilitation following gynecological operations

Presented to:
Sir Umair Shaikh

Statistics
Is the art of and science of data.
It deals with:
Planing resreach
Collecting data
Describing data
Presenting data
Analyzing data
Interperting result
Reaching decision

IMPORTANCE OF STATISTICS
It presents a fact in a definite term
It simplifies mass if figures
Its facilitates comparisons
It helps in formulating and testing hypothesis
It helps in prediction
It helps in formulation of suitable policies
Why should medical student learn biostatistics?
We have to clarify the relationship between certain factors and disease
Enumerate the occurrences of diseases
Explain the etiology of disease (which factors cause which disease)

Predict the number of disease occurrence
Read understand and criticize the medical literature
The planning , conduct and interpretation of much of medicl research are becoming increasingly reliant on statistical methods.

What is research ?
The mean is the average of all numbers and is sometimes called the arithmetic mean.
To calculate mean, add together all of the numbers in a set and then divide the sum by the total count of numbers.

Mean
The MODE is appropriate at any level of measurement.
The MEDIAN is appropriate with ordinal, interval, or ratio data.
The MEAN is appropriate when data are measured at the interval or ratio level.
The relationship between measures depends on the FREQUENCY DISTRIBUTION.
When data are normally distributed, all values will be equal.

A probability distribution is a table or an equation that links each outcome of a statistical experiment with its probability of occurrence.

TYPES OF PROBABILITY
The sampling process comprises several stages:
Defining the population of concern
Specifying a sampling frame, a set of items or events possible to measure
Specifying a sampling method for selecting items or events from the frame
Determining the sample size
Implementing the sampling plan
Sampling and data collecting
Data which can be selected

Sampling Process
TYPES OF SAMPLING
There are two major types of sampling.

Random sampling.
Non random sampling.

There are three types of simple random sampling:
Simple random sampling.
Systemic sampling
Stratified sampling.


SIMPLE RANDOM SAMPILNG
It is the random type of sampling in which each and every member has equal chance of selection.
TYPES
Simple random sample with replacement.
Simple random sample without replacement.


STRATIFIED SAMPLING
In stratified random sampling the start are formed based on members of shared characteristics random sample from each stratum is taken in a number proportional to the stratum’s size when compared to the population

There are three types of non random sampling
1) Convenience sampling
2) Quota sampling
3) Snow ball sampling

CONVENIENCE SAMPLING
Selection of which ever individuals are easiest to reach.
Is a non probability sampling technique where subjects are selected because of their convenient accessibility & proximity to the researchersexperiments.

TEST OF SIGNIFICANCE

Significance test is the process used, by researcher, to determine whether the null hypothesis is rejected, in favors of alternative research hypothesis or not.

PROPERTIES OF TEST OF SIGNIFICANCE :

It is the heart of analytical statistics depend on the role of chance.
It is divided into two types

Parametric test
Non Parametric test

Types Of Non Parametric Test :
Wilcoxon signed rank test
Wilcoxon rank test
Spearmans correlation test

Z-test:

It is used to check the association of sample with its its relevant population.
Sample size must be greater than 30.

Example:
The mean blood sugar level of 71 pt of septicemia was 160 with s.d of 0.9 and the mean blood sugar level of all pts in hospital was 122.

ANOVA Test
This test is applicable in both case that is parametric and non parametric.
When the association of more than 2 samples are checked than it is applicable as parametric.
When we check out the association more than 2 population mean than it is applicable as non parametric

ANY QUESTIONS ?? ...
QUOTA SAMPLING
Is a types of non probability sample in which the researcher selects people according to some fixed quota.
In quota sampling the researcher arms to represent the major characteristics of the population by sampling a proportional amount of each

WHAT IS STATISTICS ?
Distribution of 50 Students at the PHYSIOTHERAPY department of JINNAH hospital in Oct 2015 according to their ABO blood groups

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