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Statistics & SPSS: Course Outline

Statistics is the study of the collection, analysis, interpretation, presentation, and organization of data. In applying statistics to, e.g., a scientific, industrial, or societal problem, it is conventional to begin with a statistical population.

Course Outline

Introduction of Statistics

  • Background and definition of Statistics 
  • Descriptive and inferential statistics 
  • Variable and its type
  • Measurement scale and types 
  • Statistical data 
  • Source of data
  • Collection of data
  • Management of data by tabulation 
  • Classification
  • Graph, Charts & Histogram
  • Pie chart, Scatter diagram, Box plot and Line chart 

Sampling and Sampling Techniques

  • Concept of population and sample
  • Reasons to use sampling
  • Random number and their application
  • Sampling techniques
  • Random (simple random sampling, Systematic, stratified random sampling, Cluster sampling) and Non-random sampling (judgment sampling/purposive sampling, Convenience, Quota and snowball sampling)
  • Determination of sample size
  • Error, Sources of error and bias

Measures of Location and Dispersion

  • Measure of central tendency and its types
  • Arithmetic mean
  • Median, Mode and Geometric mean
  • Absolute and relative dispersion
  • Range & mean deviation
  • Quartile deviation
  • Standard deviation
  • Variance & significance of standard deviation
  • Coefficient of variation
  • Symmetry, Skewness and its measure

Probability and Probability Distribution

  • Introduction of probability and its uses in psychology
  • Venn diagram
  • Concept of random experiment, definition of probability and its measurement
  • Laws of probability
  • Binomial distribution
  • Poisson distribution
  • Normal distribution and its application

Course Outline

Statistical Inference

  • Introduction of inference & its types
  • Estimation and testing of Hypothesis
  • Sampling distribution of mean
  • Standard error of mean
  • Point estimation
  • Confidence interval of population mean
  • Null and alternative hypothesis, Type I & II error
  • Test of significance based on Z, t, F, χ2 distributions
  • Concept of p-value
  • Test of mean for small and large sample
  • Test for independent and paired observations
  • Inference regarding correlation and regression coefficient
  • ANOVA (Analysis of variance)

Regression and Correlation Analysis

  • Introduction to relationship
  • Scatter diagram
  • Regression analysis
  • Simple linear regression line
  • Least square method for fitting regression line
  • Simple concept of multiple regression correlation analysis
  • Simple linear correlation and correlation coefficient  
  • Coefficient of determination
  • Interpretation of correlation coefficient & association  
  • Measure of association
  • Contingency table
  • Test of independence

Non Parametric Tests

  • Introduction to distribution free procedures
  • Different types of non parametric tests like sign test
  • Wilcoxon signed rank test
  • Mann-Whitney U test
  • Kruskal-Wills (H-test) test

Data Analysis & SPSS

  • Preparation of data for analysis by using computer software SPSS

Text Books

Relevant Books