University:
Camosun College
Course:
BIOL 252 | Pathophysiology for Nursing 1
Academic year:

2024
Views:

12

Pages:

1
Author:

Aysha A.

Quantitative vs. Qualitative Data Quantitative Data Characteristics: Continuous, can be averaged or measured. Examples: Blood sugar levels (average) Hemoglobin (Hb) levels (average) Statistical Tests: Paired t-test: Used for matched data, such as before and after measurements in the same group. Unpaired t-test: Used for comparing means between two independent groups. ANOVA (Analysis of Variance): Used for comparing means across three or more groups. Qualitative Data Characteristics: Categorical, data in proportions or percentages. Examples: Number of diabetic patients (Yes/No) Number of anemic individuals (Yes/No) Statistical Tests: Chi-Square Test (χ² test): Applied to categorical data to test the association between variables. How to Decide Which Test to Apply? First Step: Pre/post test data: Paired t-test for matched data (before and after). Second Step: If the data is qualitative or categorical, apply the Chi-square test. Third Step: If the data is quantitative: For comparing two groups: Unpaired t-test. For comparing three or more groups: ANOVA. Example Analysis: Effect of Yoga on Number of Infections: Compare the effect of yoga on infection rates across different age groups or conditions using appropriate tests like ANOVA or Chi-square, depending on the nature of the data.