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Statistics in Education and Psychology

Book Description

Statistics in Education and Psychology aims to develop a coherent, logical and comprehensive outlook towards statistics. The subject involves a wide range of observations, measurements, tools, techniques and data analysis. This book covers diverse topics like measures of central tendency, measures of variability, the correlation method, normal probability curve (NPC), significance of difference of means, analysis of variance, non-parametric chi-square, standard score and T-score.

Table of Contents

  1. Cover
  2. Title page
  3. Contents
  4. Preface
  5. Chapter 1. Measures of Central Tendency
    1. Concept of Statistics
    2. Meaning and Definition of Statistics
      1. Need and Importance of Statistics
      2. The Frequency Distribution
    3. The Array
      1. Discrete Frequency Distribution
      2. Continuous Frequency Distribution
      3. Number of Classes
      4. Class Interval
      5. Class Frequency
      6. Tally Sheet
    4. Measures of Central Tendency
      1. Characteristics of an Ideal Measure of Central Value
    5. Summary
    6. Key Words
    7. References
    8. Additional Readings
  6. Chapter 2. Measures of Variability
    1. Measures of Dispersion Percentile
      1. Measures of Dispersion
      2. The Range
    2. The Quartile Deviation
    3. The Quartiles
      1. Merits and Demerits of Quartile Deviation
    4. Mean Deviation
      1. Computation of Mean Deviation from Ungrouped Data
      2. Mean Deviation from Grouped Data
      3. Merits and Demerits of Mean Deviation
    5. Variance and Standard Deviation
      1. Computation of Variance and Standard Deviation for Ungrouped Data
      2. Computation of Variance and Standard Deviation for Grouped Data
    6. Combined Variance and Standard Deviation
      1. Merits and Demerits of Standard Deviation
      2. Graphical Representation of Data
      3. The Histogram
      4. Frequency Polygon
      5. Smoothing the Frequency Polygon
      6. Cumulative Frequency Curve or Ogive
    7. Coefficient of Variation
    8. The Percentile
      1. Computation of Percentile
    9. Percentile Ranks
      1. Computation of Percentile Ranks
    10. Summary
    11. Key Words
    12. References
    13. Additional Readings
  7. Chapter 3. The Correlation Method
    1. Meaning and Concept of Correlation
    2. Methods of Correlation
      1. Scatter Diagram Method
      2. The Correlation Coefficient
      3. Pearson’s Coefficient of Correlation
      4. Direct Method
      5. Short-Cut Method
      6. Rank Difference Correlation Methods
      7. Spearman’s Coefficient of Rank Correlation
      8. Spearman’s Coefficient of Rank Difference Correlation ρ
      9. Spearman’s ρ with Tied Ranks
      10. Partial Correlation
      11. Formula to Find Partial Correlation
      12. Multiple Correlation
    3. Summary
    4. Key Words
    5. References
    6. Additional Readings
  8. Chapter 4. Normal Probability Curve
    1. The Equation of the Normal Curve
    2. Normal Probability Curve (NPC)
      1. Characteristics of the NPC
      2. NPC Table
    3. Properties of the Normal Curve
    4. Area Under the Normal Curve
    5. Implications of the Normal Curve
      1. To Determine Percentage of the Case within Given Limits
    6. Summary
    7. References
    8. Additional Readings
  9. Chapter 5. Significance of Difference of Means
    1. Statistical Inference Based on Parametric Tests
    2. Standard Error (SE)
      1. Inferences Regarding Means of Large Samples
      2. Illustration
      3. Inference Regarding Means of Small Samples
      4. Confidence Intervals and Levels of Confidence
      5. Degrees of Freedom
      6. Significance of the Difference Between Means
      7. The Significance of the Difference Between the Independent Means
      8. Large Samples
      9. Small Samples
      10. The Significance of the Difference Between the Dependent Means in Large and Small Samples
      11. The Difference Method
      12. Illustration
      13. The Method of Matching of Pairs (or Method of Equivalent Group)
      14. Important Properties of Sampling Distribution
    3. Testing of Significance
      1. Testing of Significance of Difference of Means
      2. Main Properties of t-Distribution
      3. Testing of Significance of Difference of Proportions
    4. Summary
    5. Key Words
    6. References
    7. Additional Readings
  10. Chapter 6. Analysis of Variance
    1. Analysis of Variance (ANOVA)
      1. Calculation of Sum of Squares
      2. Summary-Analysis of Variance
      3. Tests of Differences by the Use of t-Test
      4. Assumptions of ANOVA
    2. Summary
    3. Key Words
    4. References
    5. Additional Readings
  11. Chapter 7. Non-Parametric Test-Chi-square
    1. Nature of Non-Parametric Tests
    2. Chi-Square (χ2) Test
    3. Characteristics of Chi-Square
    4. Uses of Chi-Square
    5. Test of Goodness of Fit
    6. Testing the Divergence of Observed Results from Those Expected on the Hypothesis of Equal Probability
      1. Testing the Divergence of Observed Results from Those Expected on the Hypothesis of Normal Probability
      2. Test of Independence
    7. Computation of Chi-Square When Variables are in 2 × 2 Fold Contingency Table
    8. Computation of Chi-Square When Frequencies are Small
    9. Summary
    10. Key Words
    11. References
    12. Additional Readings
  12. Chapter 8. Standard Score and T-Score
    1. Need of Common Scales
      1. Standard Scores (SS)
    2. Conversion of Raw Scores to Standard Scores
    3. Normalizing the Frequency Distribution: the T-Scale
    4. Derivation of T-Scale Equivalents for Raw Scores
    5. Advantages of Standard Scores and T-Scores
    6. Summary
    7. Key Words
    8. References
    9. Additional Readings
  13. Bibliography
  14. Annexure-I
  15. Annexure-II
  16. Annexure-III
  17. Annexure-IV
  18. Annexure-V
  19. Annexure-VI
  20. Copyright