Computer assistance in statistical methods.28.04.2021
- 1. BASIC WORKSHOP OF RESEARCH METHODOLOGY MUHS,NASHIK COMMON STATISTICAL SOFTWARE’S AND ITS APPLICATIONS Dr. Anjali Upadhye M.Sc.(Statistics),M.B.A.,PGDTQM,Ph.D. Head of Department,Research ,ADAMC,Ashta (Contact :+91 9922494537 , anjaliupadhye1511@gmail.com) 1
- 2. COMMON STATISTICAL SOFTWARE’S AND ITS APPLICATIONS LEARNING OBJECTIVES – Introduction – Features of Statistical software – MS-EXCEL – SPSS: Statistical Package for the Social Sciences – EPI INFO – SAS: Statistical Analysis System – E-views: Statistical Package for windows – MINITAB – STATA – R & MATLAB – PSPP – G POWER TOOLS – REVMAN software for systematic review – Write about other Statistical related Software’s 2 www.statsanjal.in
- 3. Introduction ■ Statistical analysis is the science of collecting, exploring and presenting large amounts of data to discover underlying patterns and trends and these are applied every day in research, industry and government to become more scientific about decisions that need to be made. Statistical software’s helps in analysis of data. ■ The software can either read data directly from EXCEL spreadsheet, a user can enter the data directly to software, or has specialized data entry software to capture data. ■ The statistical software’s then manipulates the information they possess to discover patterns which can help the user uncover the predictions and help to interpret the data. 3 www.statsanjal.in
- 5. Initial steps to enter Statistical Software’s in research project ■ Getting your data ready to enter into the software. ■ Defining and labeling variable ■ Entering data appropriately with each row containing each case and each column as variable. ■ Data checking and cleaning is possible. – All data should be numeric, although it may not be all variables it is not desirable to use letter or word (String variable) as data. This can be achieved by recoding the letter or word (string data) into desirable numeric and labeled appropriately. – Data exploration can be done to check for errors and other accuracy. – The statistical level of significance for rejecting null hypothesis (Ho) is when your p-value significance is less than0.05. 5 www.statsanjal.in
- 6. MS-EXCEL ■ This is part of the Microsoft Office suite of programs. Excel version 1.0 was first released in 1985, with the latest version Excel 2016.Microsoft Excel 2010 is one of the most popular software applications worldwide and is part of the Microsoft Office 2010 productivity suite. ■ You can use Excel to analyze data, for example, in accounts, budgets, billing and many other areas. ■ Excel allows you to explore the menu bar and the different tasks that can be done with it. ■ You can work on sample spreadsheets doing basic math, adding and deleting columns and rows, and preparing the worksheet for printing. ■ You can run your data visually to show trends, patterns and comparisons between the data in a chart, table or other template, and Excel performs most general statistical analyses but weak in regression, logistic regression, survival analysis, analysis of variance, factor analysis, multivariate analysis. 6 www.statsanjal.in
- 7. SPSS: STATISTICAL PACKAGE FOR THE SOCIAL SCIENCES ■ SPSS stands for Statistical Package for the Social Sciences. It was one of the earliest statistical packages with Version 1 being released in 1968, well before the advent of desktop computers. ■ SPSS assists the user in describing data, testing hypotheses and looking for a correlation or relationship between one or more variables. SPSS is very suitable for most regression analysis and different kinds of ANOVA (regression, logistic regression, survival analysis, analysis of variance, factor analysis, multivariate analysis but not suitable for time series analysis and multilevel regression analysis)-Wikipedia (2014). 7 www.statsanjal.in
- 8. EPI INFO Epi Info is public domain statistical software for epidemiology developed by Centers for Disease Control and Prevention (CDC) in Atlanta, Georgia (USA). Epi Info has been in existence for over 20 years and is currently available for Microsoft windows. http://www.cdc.gov/epiinfo. 8
- 9. SAS: STATISTICAL ANALYSIS SYSTEM ■ SAS - SAS stands for Statistical Analysis System. ■ It was developed at the North Carolina State University in 1966, so is contemporary with SPSS &which has its latest version produced in December 2011 is a package that many "power users" like because of its power and programmability. ■ SAS is one of the packages that are difficult to learn. ■ To use SAS, you must write SAS programs that manipulate your data and perform your data analyses. ■ SAS performs most general statistical analyses (regression, logistic regression, survival analysis, analysis of variance, factor analysis, multivariate analysis). The greatest strengths of SAS are probably in its ANOVA, mixed model analysis and multivariate analysis, while it is probably weakest in ordinal and multinomial logistic ■ Regression (because these commands are especially difficult), and robust methods (it is difficult to perform robust regression, or other kinds of robust methods) 9 www.statsanjal.in
- 10. E-VIEWS: STATISTICAL PACKAGE FOR WINDOWS E-Views is a statistical package for window, used mainly for time-series oriented econometrics analysis. EViews can be used for general statistical analysis and econometric analyses, such as cross-section and panel data analysis and time series estimation and forecasting. EViews relies heavily on a proprietary and undocumented file format for data storage. 10
- 11. MINITAB & MATLAB ■ MINITAB is statistical software used by educators, students, scientists, business associates and researchers to provide statistical software in a multitude of areas. MINITAB, developed around 1990, and remains one of the oldest statistical software programs available. MINITAB has compatibility with PC, Macintosh, Linux and all other major platforms. ■ MINITAB performs most general statistical analyses (regression, logistic regression, survival analysis, analysis of variance, factor analysis, but has its weaknesses in general linear model (GLM) and Multilevel regression). 11 www.statsanjal.in
- 12. STATA ■ Stata is a more recent statistical package with Version 1 being released in 1985. Since then, it has become increasingly popular in the areas of epidemiology and economics, and probably now rivals SPSS and SAS in it user base. ■ STATA is a powerful statistical package with smart data-management facilities, a wide array of up-to-date statistical techniques, and an excellent system for producing publication-quality graphs ■ STATA performs most general statistical analyses (regression, logistic regression, survival analysis, analysis of variance, factor analysis, multivariate analysis and time series analysis). 12 www.statsanjal.in
- 13. R & MATLAB R ■ S-plus is a statistical programming language developed in Seattle in 1988. R is a free version of S- plus developed in 1996. Since then, the original team has expanded to include dozens of individuals from all over the globe. Because it is a programming language and environment, it is used by giving the software a series of commands, often saved in text documents called syntax files or scripts, rather than having a menu-based system. Because of this, it is probably best used by people already reasonably expert at statistical analysis, or who have an affinity for computers. Good points ■ Very powerful – easily matches or even surpasses many of the models found in SAS or Statas ■ Researchers around the world write their own procedures in R, which are then available to all users ■ Free! At http://cran.csiro.au/ 13 www.statsanjal.in
- 14. Effect Size Calculations: Example 14 www.statsanjal.in
- 15. Sample Size Calculation with G Power* 15 www.statsanjal.in
- 16. Reliability Analysis (Normality Check) Variables Reliability Statistics Normality Cronbach's Alphaa Cronbach's Alpha Based on Standardized Items N of Items Demographic Characteristics about Purchase of Green Products 0.463 0.474 5 Deviated Consumer's Awareness about the green products 0.927 0.911 19 Normal Green products purchased by the Consumers 0.959 0.962 10 Normal Reasons for purchase of green products 0.875 0.804 7 Normal Influencing key aspects of green products 0.888 0.895 13 Normal Influencing factors for purchase decision of green products 0.483 0.165 7 Deviated Consumer behavioral perceptions regarding value of being ecofriendly 0.977 0.977 13 Normal Consumer Attitude regarding Green Products 0.900 0.899 13 Normal Opportunities available in future -0.082 0.068 5 Deviated 16 www.statsanjal.in
- 17. Paired t Test with SPSS 17 www.statsanjal.in
- 18. Other Software’s for Research Support ■ http://www.unisa.edu.au/Health- Sciences/Research/Biostatistical-and- epidemiological-support/ ■ https://www.surveymonkey.com/ ■ http://www.epidata.dk/download.php ■ http://www.gpower.hhu.de/en.html ■ www.samplesurvey.com ■ https://www.gnu.org/software/pspp/get.html 18 www.statsanjal.in
- 19. Meet me on : www.statsanjal.in 19 www.statsanjal.in
- 20. 1. http://www.statsanjal.in 2. http://www.ijooar.com Contact :9922494537 anjaliupadhye1511@gmail.com 20 www.statsanjal.in