Selection of appropriate statistics and tools
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This document provides an overview of selecting appropriate statistics and tools for research. It discusses various types of statistical analysis including descriptive analysis, inferential analysis, differences analysis, association analysis, and predictive analysis. Descriptive analysis involves summarizing data through tables, graphs, and numerical measures of central tendency, variation, and distribution. Inferential analysis makes conclusions about a population based on a sample. Differences analysis examines whether two or more groups are the same or different. Association analysis looks at relationships between variables. Predictive analysis forecasts one variable based on others. The document also explains when to use parametric versus non-parametric statistics depending on factors like sample size, distribution, and scale of measurement.
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Selection of appropriate statistics and tools
- 1. Selection of Appropriate Statistics and Tools Dr. Suresh Kumar Murugesan PhD
- 2. About the Presenter ● Dr.Suresh Kumar Murugesan is a passionate Professor,researcher and Mental Health Practitioner from Madurai,Tamil Nadu,India ● At present he is Heading the department of Psychology,The American College,Madurai and Adjunct Professor of School of Behavioural Sciences and Education at TAU ● He is the State President of World Congress of Psychologists (WCOP) and he is very keen in learning new research studies in behavioural Sciences and open to learn. ● His ultimate aim is to make impression in the field of Knowledge ● His area of specializations are Psychometry,Positive Psychology
- 3. Disclaimer ● This presentation is prepared for learning purpose only and all the images and pictures used in this presentation are taken from google image search. ● Due recognition was given to all the material collected from the various sources. ● Any name or reference is missed kindly bring it to the notice of the presenter for inclusion. ● Email - sureshkumar800@yahoo.com Thank you
- 4. WHICH LIST CORRECT? WHY? LIST - A 1. 1, ii, 3, four, v, 6….. 2. I, 2, III, iv, 5, six…. 3. 1, 2, 3, 4, v, 6…. 4. i, ii, 3, 4, v, VI…. LIST - B 1. 1, 2, 3, 4, 5, 6 …… 2. i, ii, iii, iv, v, vi…… 3. I, II, III, IV, V, VI….. 4. ONE, TWO, THREE, FOUR, FIVE,….
- 5. WHAT IS TOOL? List 1 List 2
- 6. NAME SOME OF THE STATISTICAL TOOLS
- 7. WHAT IS STATISTICAL TOOL?
- 8. STATISTICAL TOOLS AND TECHNIQUES 1. Parametric 2. Non- Parametric
- 9. WHY STATISTICS IN RESEARCH? 1. Statistical methods involved in carrying out a study include planning, designing, collecting data, analysing, drawing meaningful interpretation and reporting of the research findings. Statistics Planning Designing Collecting Data Analyzing Drawing Meaningful Interpretation Reporting
- 10. WHY STATISTICS IN RESEARCH? 1. The statistical analysis gives meaning to the meaningless numbers, thereby breathing life into a lifeless data. 2. The results and inferences are precise only if proper statistical tests are used.
- 11. FEW MORE QUESTIONS ????? (VARIABLE) Which statistical technique will you use? Why? 1. To find out the influence of one variable on other variable 2. To find out the association between variables 3. To find our the relationship between two variables? 4. To find out the level of study variable ●
- 12. FEW MORE QUESTIONS ????? (SAMPLE) Which statistical technique will you use? Why? 1. If the sample size is less than 10 2. For random sample 3. Non random sample 4. Homogeneous sample and heterogeneous sample ●
- 13. FEW MORE QUESTIONS ????? (SCALES) Which statistical technique will you use? Why? 1. For ratio scale data 2. For interval scale data 3. For ordinal scale data 4. For nominal scale data ●
- 22. When to Use? Parametric 1. When the distribution is normal 2. Large Sample 3. Interval and Ratio distributions 4. Random sampling 5. When decided to make an assumptions Nonparametric 1. when the distribution is not normal 2. Small Sample 3. Nominal and ordinal distribution 4. Non Random sampling 5. When it is not make an assumptions
- 32. Types of Data
- 34. NPC
- 44. TYPES OF STATISTICAL ANALYSIS Dr. Suresh Kumar Murugesan PhD +91 7904865059 sureshkumar800@yahoo.com Madurai, Tamil Nadu, India Madurai, Meenakshi Amman Temple
- 45. LEARNING OUTCOME At the end of the session the learners will be able to understand and apply in their field 1. Types of statistical Analysis ○Descriptive Data Analysis ○Inferential Statistical Analysis ○Difference Statistical Analysis ○Association Statistical Analysis ○Predictive Statistical Analysis 2. When to use parametric and non parametric?
- 46. Types of Statistical Analysis
- 47. TYPES OF STATISTICAL ANALYSIS Types of Statistical Analysis Descriptive What are the characteristics of the respondents? Inferential What are the characteristics of the population? Differences Are two are more groups same or different? Association Are two or more variables related in a systematic way? Predictive Can we predict one variable if we know one or more other variables in the study?
- 49. Descriptive Statistical Analysis Tables Frequency Distribution Graphs Bar Diagram Pie Diagram Line Graph Histogram Numbers Centre Mean, Median, Mode Important Points Median, Quartiles, Deciles, Percentiles Variation Range, Variance, Standard Deviation Distribution Skewness and Kurtosis
- 50. Descriptive Analysis - Tables
- 51. EXAMPLE -1 Simple Table Cross Tabulation
- 52. EXAMPLE -2
- 53. Descriptive Analysis - Graphs
- 55. GRAPHS – EXAMPLE 1 Bar Diagram Histogram Diagram
- 56. GRAPHS – EXAMPLE 2 Line Graph Pie Diagram
- 57. Descriptive Analysis – Numbers (Centre)
- 58. EXAMPLE – MEAN, MEDIAN AND MODE
- 60. Descriptive Analysis – Numbers (Important Points)
- 61. EXAMPLE MEDIAN AND QUARTILE Median Quartile
- 65. Descriptive Analysis – Numbers (Variance)
- 66. Example of samples from two populations with the same mean but different dispersion. The blue population is much more dispersed than the red population.
- 67. EXAMPLE - RANGE
- 68. EXAMPLE – STANDARD DEVIATION
- 70. Descriptive Analysis – Numbers (Distribution)
- 71. EXAMPLE FOR SKEWNESS AND KURTOSIS
- 73. What is Inferential Statistics?
- 77. Descriptive Vs inferential Statistics
- 82. Differences Statistical Analysis Parametric Paired ‘t’ Test Unpaired ‘t’ Test ‘F’ Test Non- Para metric Wilcoxon Rank sum test Mann-Whitney U test Kruskal Wallis Test
- 84. Association Statistical Analysis Parametric Product moment Order Correlation Non- Para metric Rank Order Correlation
- 86. Predictive Statistical Analysis Parametric/ Non- Para metric Regression Analysis Discriminant Function Analysis
- 87. When to Use Parametric or Non parametric Statistics?
- 90. WHEN TO USE? Parametric 1. Decided to make assumption about the Population 2. Probabilistic distribution is normal 3. Sampling is based on probability or randomness 4. Data collected on the scale of interval or ratio 5. Large Sample size 6. Homogeneous data 7. Independent data set Non Parametric 1. Don’t make assumption but describe 2. Distribution is arbitrary or not normal 3. Sampling is non probability or non randomness 4. Data collected on the scale of nominal or interval 5. Small Sample size 6. Homogeneous and Heterogeneous data 7. Any data set
- 91. UNDERSTANDING THE TERMS IN STATISTICS
- 92. Thank you