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By
Dr. Kanagaraj Easwaran
Associate Professor
Department of Social Work
School of Social Sciences
Mizoram University
Aizawl -796 004.
 What is analysis
 Explaining the one with the other
 Association
 Relationship: Linear vs Non linear
 Comparison: Two or More Groups
 Hypothesis Testing
Parametric vs Non Parametric Tests
◦ Parameter – Population measure
 Mean, Standard Deviation, Proportion
◦ Statistic – Sample measure
Mean, Standard Deviation, Proportion
◦ Nominal or Classificatory Scale
 Gender, Locality, Religion, District, Block, State
 Frequency, Mode,
◦ Ordinal or Ranking Scale
 Beauty, Military Ranks, Product Preference
 Median,
◦ Interval Scale
 Celsius or Fahrenheit, Likert Scale, Rating Scale
 Arithmetic Mean
◦ Ratio Scale
 Kelvin temperature, Speed, Height, Mass or Weight,
 Income, Expenditure, Age
 Geometric Mean, Arithmetic Mean
 Observations must be independent
 Measurement at Interval or Ratio level
 Observations drawn from Normally distributed
populations
 Populations must have the same variances
 Sampling: Random or Representative
 Distribution Free tests
◦ No assumption of normality or homogeneity
 No requirement of strong measurement
◦ nominal or ordinal level
 Less powerful than parametric tests
 Every parametric test has non-parametric counter
part
 Parametric tests preferable when assumptions are
satisfied
  Parametric Non-parametric
Assumed distribution Normal Any
Assumed variance Homogeneous Any
Typical data Ratio or Interval Ordinal or Nominal
Data set
relationships
Independent Any
Usual central
measure
Mean Median
Benefits
Can draw more
conclusions
Simplicity; Less
affected by outliers
  Parametric Non-parametric
Correlation test Pearson Spearman
Independent
measures, 2 groups
Independent- t-test
Mann-Whitney test
Independent
measures, >2 groups
One-way ANOVA Kruskal-Wallis test
Repeated measures,
2 conditions
Matched-pair t-
test
Wilcoxon test
Repeated measures,
>2 conditions
One-way,
repeated
measures ANOVA
Friedman's test
 Univariate: Descriptive Statistics
 Bivariate
 Multivariate
Dr.E.Kanagaraj
mekanagaraj@gmail.com
Cell:9436362333

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07 data analysis

  • 1. By Dr. Kanagaraj Easwaran Associate Professor Department of Social Work School of Social Sciences Mizoram University Aizawl -796 004.
  • 2.  What is analysis  Explaining the one with the other  Association  Relationship: Linear vs Non linear  Comparison: Two or More Groups  Hypothesis Testing
  • 3. Parametric vs Non Parametric Tests ◦ Parameter – Population measure  Mean, Standard Deviation, Proportion ◦ Statistic – Sample measure Mean, Standard Deviation, Proportion
  • 4. ◦ Nominal or Classificatory Scale  Gender, Locality, Religion, District, Block, State  Frequency, Mode, ◦ Ordinal or Ranking Scale  Beauty, Military Ranks, Product Preference  Median, ◦ Interval Scale  Celsius or Fahrenheit, Likert Scale, Rating Scale  Arithmetic Mean ◦ Ratio Scale  Kelvin temperature, Speed, Height, Mass or Weight,  Income, Expenditure, Age  Geometric Mean, Arithmetic Mean
  • 5.  Observations must be independent  Measurement at Interval or Ratio level  Observations drawn from Normally distributed populations  Populations must have the same variances  Sampling: Random or Representative
  • 6.  Distribution Free tests ◦ No assumption of normality or homogeneity  No requirement of strong measurement ◦ nominal or ordinal level  Less powerful than parametric tests  Every parametric test has non-parametric counter part  Parametric tests preferable when assumptions are satisfied
  • 7.   Parametric Non-parametric Assumed distribution Normal Any Assumed variance Homogeneous Any Typical data Ratio or Interval Ordinal or Nominal Data set relationships Independent Any Usual central measure Mean Median Benefits Can draw more conclusions Simplicity; Less affected by outliers
  • 8.   Parametric Non-parametric Correlation test Pearson Spearman Independent measures, 2 groups Independent- t-test Mann-Whitney test Independent measures, >2 groups One-way ANOVA Kruskal-Wallis test Repeated measures, 2 conditions Matched-pair t- test Wilcoxon test Repeated measures, >2 conditions One-way, repeated measures ANOVA Friedman's test
  • 9.  Univariate: Descriptive Statistics  Bivariate  Multivariate