standard statistical tools in research and data analysis
DESCRIPTION
Statistics is a field of science concerned with gathering, organizing, analyzing, and extrapolating data from samples to the entire population. This necessitates a well-designed study, a well-chosen study sample, and a proper statistical test selection. A good understanding of statistics is required for the correct design of an epidemiological research or a clinical trial. Improper statistical approaches might lead to erroneous findings and unethical behavior. Read More with Us: https://bit.ly/3ApSEeT Why Statswork? Plagiarism Free | Unlimited Support | Prompt Turnaround Times | Subject Matter Expertise | Experienced Bio-statisticians & Statisticians | Statistics across Methodologies | Wide Range of Tools & Technologies Supports | Tutoring Services | 24/7 Email Support | Recommended by Universities Contact Us: Website: www.statswork.com Email: [email protected] #UnitedKingdom: +44 1618184707 #India: +91 4446313550 WhatsApp: +91 8754467066TRANSCRIPT
Standard StatisticalTools in Research andData Analysis
An Academic presentation by Dr. Nancy Agnes, Head, Technical Operations, Statswork Group www.statswork.comEmail: [email protected]
Variables
Quantitative variables
Statistics
Descriptive statistics
Inferential statistics
Software for Statistics, Sample Size Calcuation &
Power Analysis
Summary
Outline
TODAY'S DISCUSSION
Statistics is a field of science concerned withgathering, organising, analysing, and extrapolatingdata from samples to the entire population.
This necessitates a well-designed study, a well-chosen study sample, and a proper statistical testselection.
A good understanding of statistics is required for thecorrect design of an epidemiological research or aclinical trial.
Improper statistical approaches might lead toerroneous findings and unethical behaviour.
INTRODUCTION
A variable is a trait that differs from one personto the next within a population.
Quantitative variables are measured by a scaleand provide quantitative information, such asheight and weight.
Qualitative factors, such as sex and eye colour,provide qualitative information
VARIABLES
Figure 1. Classification of variables [1]
Discrete and continuous measures are used to split quantitative ornumerical data.
Continuous data can take on any value, whereas discrete numerical datais stored as a whole number such as 0, 1, 2, 3,... (integer).
Discrete data is made up of countable observations, while continuousdata is made up of measurable observations.
Discrete data examples include the number of respiratory arrest episodesor re-intubation in an intensive care unit.
QUANTITATIVE VARIABLES
Contd...
Continuous data includes serial serumglucose levels, partial pressure ofoxygen in arterial blood, andoesophageal temperature.
A hierarchical scale based oncategory, ordinal, interval and ratioscales with increasing precision can beused
Descriptive statistics try to explain how variables in a sample orpopulation are related.
The mean, median, and mode forms, descriptive statistics give anoverview of data.
To characterise and infer about a community as a whole,inferential statistics use a random sample of data from that group.
It's useful when it's not possible to investigate every singleperson in a group.
STATISTICS
The central tendency describes howobservations cluster about a centrepoint, whereas the degree of dispersiondescribes the spread towards theextremes.
DESCRIPTIVE STATISTICS
In inferential statistics, data from a sample isanalysed to conclude the entire population.
The goal is to prove or disprove the theories.
A hypothesis is a suggested explanation for aphenomenon (plural hypotheses).
Hypothesis testing is essential to process formaking logical choices regarding observedeffects' veracity.
INFERENTIAL STATISTICS
There are several statistical software packages accessible today.
The most commonly used software systems are StatisticalPackage for the Social Sciences (SPSS – manufactured by IBMcorporation), Statistical Analysis System (SAS – developed bySAS Institute North Carolina, Minitab (developed by Minitab Inc),United States of America), R (designed by Ross Ihaka and RobertGentleman from the R core team), Stata (developed byStataCorp), and MS Excel.
SOFTWARES FOR STATISTICS, SAMPLE SIZECALCULATION AND POWER ANALYSIS
StatPages.net - contains connections to a variety of online power calculators.
G-Power — a downloadable power analysis software that works on DOS.
ANOVA power analysis creates an interactive webpage that estimates the poweror sample size required to achieve a specified power for one effect in a factorialANOVA design.
Sample Power is software created by SPSS. It generates a comprehensive reporton the computer screen that may be copied and pasted into another document.
There are several websites linked to statistical power studies. Here are a fewexamples:
A researcher must be familiar with the mostimportant statistical approaches for doingresearch.
This will aid in the implementation of a well-designed study that yields accurate and validdata.
Incorrect statistical approaches can result inerroneous findings, mistakes, and reducedpaper's importance.
SUMMARY
Contd...
Poor statistics can lead to poor research, which can lead toimmoral behaviour.
As a result, proper statistical understanding and the rightapplication of statistical tests are essential.
A thorough understanding of fundamental statisticalmethods will go a long way toward enhancing study designsand creating high-quality medical research that may be usedto develop evidence-based guidelines.
