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Swayam

Advanced Statistics in Education

via Swayam

Overview

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ABOUT THE COURSE:Statistics is very important in Social Science researches as it enables the researchers to select the favorable research topic in line with the statistical techniques which further facilitate the selection of sample, to collect the requisite data, to analyse the data, to test the hypotheses and to draw the right conclusion. It also helps in examining the relationship between various variables and to assess the impact of various policies. Statistics is taught in almost all the graduate and post graduate programmes in social sciences to enable the learners to handle the data and to make the right inferences. The NEP 2020 intends to shift the paradigm of higher education from rote memorization to understanding and application and it also emphasizes on making the learners independent thinkers. In this course basic concepts of statistics like graphical representation of data; Mean, Median and Mode; measures of variability; Parametric and Non-parametric test; Correlation; Regression and Properties of Normal Probability Curve have been discussed. This course has been designed in such a way that besides the theoretical concepts, it provides ample opportunities for the learners for hand on practices. It is expected that after attending this course they will be able to understand the above mentioned basic concepts of Statistics and they will effectively apply it whenever the need arises.INTENDED AUDIENCE:Students Pursuing Diploma and Postgraduate Diploma, B.Ed/ M.Ed/ BA (FYUP, Any Discipline)/ MA (Any Discipline), BA.B.Ed/ B.Sc.B.Ed & B.Com.B.EdPREREQUISITES: Qualified class XII in any disciplineINDUSTRY SUPPORT:NA

Syllabus


Week 1
  • Definition and Characteristics of statistics
  • Types and Scope of statistics
  • Importance and use of Statistics in Social Science Researches
  • Basic concepts related to Population, Sample, Parameter, Statistic and Inference
  • Types and levels of data
Week 2
  • Organisation of data
  • Hands on practices on organization of data
  • Graphical presentation of data
  • Pie chart, Histogram, Frequency Polygon and Ogive
  • Hands on practices on Graphical Presentation of data
Week 3
  • Measures of Central Tendency
  • Meaning of Mean, Median and Mode
  • Relationship among Mean, Median and Mode
  • Computation of Mean from ungrouped data
  • Computation of Median and Mode from the ungrouped data
Week 4
  • Hands on practices on computations of mean from grouped data-I
  • Hands on practices on computations of mean-II
  • Hands on practices on computations of median-I
  • Hands on practices on computations of median-II
  • Hands on practices on computations of mode from the grouped data
Week 5
  • Measures of variability
  • Meaning of AD, MD, SD and QD
  • Computation of AD, MD from the ungrouped data
  • Computation of SD and QD from the ungrouped data
  • The significance and use of various measures of variability
Week 6
  • Hands on practices on Computation of AD, and MD from grouped data.
  • Hands on practices on Computation of SD-I.
  • Hands on practices on Computation of SD-II.
  • Hands on practices on Computation QD-I
  • Hands on practices on Computation QD- II.
Week 7
  • Parametric and Non-parametric Tests
  • Types of Parametric and Non-parametric Tests
  • Differences between Parametric and Non-parametric Tests
  • Basic assumptions of Parametric and Non-parametric Tests
  • Uses of Parametric and Non-parametric Tests
Week 8
  • Concept & Types of Hypotheses
  • Testing the Null-hypotheses
  • Significance of difference between means
  • Chi-square test assumptions
  • Hands on practices on Chi-square test
Week 9
  • Concept & Assumption of t-test
  • Hands on practices on applying t-test
  • Concept & Assumption of ANOVA
  • Hands on practices on applying ANOVA- I
  • Hands on practices on applying ANOVA- II
Week 10
  • Meaning, types & significance of correlation
  • The coefficients of correlation
  • Hands on practices on computation of correlation by Spearman's method
  • Hands on practices on computation of correlation by Pearson's method-1
  • Hands on practices on computation of correlation by Pearson's method- II
Week 11
  • Meaning and significance of regression & prediction
  • Accuracy of predictions from regression equation
  • Hands on practices on regression equation- I
  • Hands on practices on regression equation- II
  • Hands on practices on regression equation- III
Week 12
  • Normal probability Curve: Meaning and Importance
  • Characteristics of Normal probability Curve
  • Uses of Normal probability Curve- I
  • Uses of Normal probability Curve- II
  • Uses of Normal probability Curve- III

Taught by

Dr. Sajid Jamal

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