Statistical Treatment in Quantitative Research

Introduction

• Topic of discussion: Statistical treatment in quantitative research
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Types of Statistical Treatment

1. Descriptive Statistics

   • Used to summarize and describe data.
   • Common measures:
     • Mean: Arithmetic average of the distribution.
     • Median: Middle value that separates higher and lower values.
     • Mode: Most frequently occurring value.
   • Measures of variability:
     • Standard Deviation: Measure of dispersion around the mean.
     • Variance: Square of the standard deviation.
     • Range: Difference between maximum and minimum scores.
   • Other measures:
     • Frequency: Count of occurrences.
     • Percentage: Representation of counts.

2. Inferential Statistics

   • Used to make inferences about a population based on sample data.
   • Common tests:
     • T-Test: Compares means of two groups.
       • Types:
         • Independent sample T-Test: Compares two separate populations.
         • Paired sample T-Test: Compares two measures within a single population.
     • ANOVA (Analysis of Variance): Used when comparing means of three or more groups.
       • Special case of ANOVA when only two groups are involved.
     • Correlation: Examines relationships between two different variables.

Descriptive Statistics Explained

• Measure of Central Tendency
  • Mean, Median, Mode.
• Measure of Variability
  • Standard Deviation, Variance, Range.

Inferential Statistics Explained

• T-Test:
  • Independent sample: Two separate groups (e.g., experimental vs. control).
  • Paired sample: Same group measured at two different times (e.g., pre-test vs. post-test).
• ANOVA:
  • Used when comparing three or more groups.
• Correlation:
  • Examines the relationship between variables (e.g., scores vs. height).

Examples of Statistical Treatments

Example 1: Experimental Study

• Question 1: What is the academic achievement before exposure to methods?

  • Treatment: Descriptive (Mean, Standard Deviation).

• Question 2: Significant differences in achievement before and after exposure?

  • Treatment: T-Test (Paired sample).

• Question 3: Differences between two methods?

  • Treatment: T-Test (Independent sample).

Example 2: Factors Affecting Mathematics Achievement

• Question 1: What are the levels of motivation?

  • Treatment: Descriptive (Mean, Standard Deviation).

• Question 2: Significant differences between high and low motivation?

  • Treatment: T-Test (Independent sample).

• Question 3: Significant relationship between motivation and achievement?

  • Treatment: Correlation.

Example 3: Impact of Multimedia

• Question 1: What is the impact of using multimedia?

  • Treatment: Descriptive.

• Question 2: Significant differences between pre and post measures?

  • Treatment: T-Test (Paired sample).

Example 4: Effectiveness of Instructional Strategies

• Question 1: Level of performance before and after instruction?

  • Treatment: Descriptive.

• Question 2: Significant difference before and after?

  • Treatment: Paired sample T-Test.

• Question 3: Comparing effectiveness among three strategies?

  • Treatment: ANOVA.

Conclusion

• Overview of statistical treatment in quantitative research.
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