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PR-2-CHAPTER-5.pptx

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This document discusses different methods for correlating and comparing data sets. It describes four types of correlation - Pearson, point-biserial, Spearman rank-order, and chi-square test of independence - that determine how variables relate. The Pearson correlation is used for interval/ratio scales, point-biserial for dichotomous and continuous variables, Spearman for ranked data, and chi-square for categorical frequencies. Methods for comparing means include t-tests for independent and dependent samples to analyze two groups, and ANOVA to analyze three or more groups.

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CHAPTER 5
PR-2-CHAPTER-5.pptx
CORRELATING TWO DATA SETS TYPES OF CORRELATION
? Determines how one variables varies relatively with the other. ? Causal relationship means that a change in one variable affects the other variable.
? Pearson Product-Moment Correlation ? Point-Biserial Correlation ? Spearman Rank-Order Correlation ? Chi-Square Test of Independence
Pearson product-moment correlation, or Pearson¡¯s r, is used to determine the relationship between data in the interval or ratio scale.
When a variable in an interval or ratio scale (e.g., achievement in mathematics) is correlated with naturally-occurring dichotomous variable like gender (male or female).
When ranking attributes is more meaningful than its interval or ratio measures, such as in giving academic honors, the participants are ranked
This test is utilized when correlating two data sets expressed in frequency counts and when the variables are categorical.
COMPARING TWO GROUP MEANS - Before comparing two sets of data, the fact that data may be independent or dependent must be considered. - The purpose of comparing two group means is to know whether they are statistically equal or different.
t-Test for Independent Samples - To determine if there is a significant difference between the means of two independent groups of participant, the t-test for independent samples is used.
- The t-Test must be used to confirm if there exists a statistical difference t-Test for Dependednt Samples or Paired Sample t-Test - The t-Test for dependent samples and the t-Test for independednt samples are used and interpreted in the same manner.
- The only difference is that in the t-Test for dependent samples, the two sets of data compared come from the group of individuals or research elements.
COMPARING THREE OR MORE GROUP MEANS - The F-test, commonly known as analysis of variance (ANOVA), is used to compare three or more means. - It requires a further statistical analysis when a significant F-value is calculated.
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PR-2-CHAPTER-5.pptx

  • 3. CORRELATING TWO DATA SETS TYPES OF CORRELATION
  • 4. ? Determines how one variables varies relatively with the other. ? Causal relationship means that a change in one variable affects the other variable.
  • 5. ? Pearson Product-Moment Correlation ? Point-Biserial Correlation ? Spearman Rank-Order Correlation ? Chi-Square Test of Independence
  • 6. Pearson product-moment correlation, or Pearson¡¯s r, is used to determine the relationship between data in the interval or ratio scale.
  • 7. When a variable in an interval or ratio scale (e.g., achievement in mathematics) is correlated with naturally-occurring dichotomous variable like gender (male or female).
  • 8. When ranking attributes is more meaningful than its interval or ratio measures, such as in giving academic honors, the participants are ranked
  • 9. This test is utilized when correlating two data sets expressed in frequency counts and when the variables are categorical.
  • 10. COMPARING TWO GROUP MEANS - Before comparing two sets of data, the fact that data may be independent or dependent must be considered. - The purpose of comparing two group means is to know whether they are statistically equal or different.
  • 11. t-Test for Independent Samples - To determine if there is a significant difference between the means of two independent groups of participant, the t-test for independent samples is used.
  • 12. - The t-Test must be used to confirm if there exists a statistical difference t-Test for Dependednt Samples or Paired Sample t-Test - The t-Test for dependent samples and the t-Test for independednt samples are used and interpreted in the same manner.
  • 13. - The only difference is that in the t-Test for dependent samples, the two sets of data compared come from the group of individuals or research elements.
  • 14. COMPARING THREE OR MORE GROUP MEANS - The F-test, commonly known as analysis of variance (ANOVA), is used to compare three or more means. - It requires a further statistical analysis when a significant F-value is calculated.