Use code: AXEUSCESTUDENT2025 for 10% off your next purchase!

Research Forum

Use code: AXEUSCE-AI for 10% off your next purchase!

Continuous Variable...
 
Notifications
Clear all

Continuous Variable Analyses

1 Posts
1 Users
0 Reactions
16 Views
(@rahima-noor)
Posts: 37
Member Moderator
Topic starter
 

This forum is dedicated to understanding and discussing the statistical tests commonly used for analyzing continuous variables. Topics covered include the Student’s t-test, Mann–Whitney U test, and Wilcoxon signed-rank test.

🧪 1. Student’s t-test

Description:
The Student’s t-test is a parametric test used to compare the means between two groups.

Types:

  • Independent t-test: Compares means of two independent groups (e.g., treatment vs. control).

  • Paired t-test: Compares means of the same group at different times (e.g., before and after treatment).

Assumptions:

  • Data is continuous and normally distributed.

  • Homogeneity of variances.

  • Observations are independent.

Common Use Case:
Comparing mean systolic blood pressure between two treatment groups.

Discussion Thread Ideas:

  • How to test for normality before using the t-test?

  • What to do if assumptions are violated?

⚖️ 2. Mann–Whitney U Test (Wilcoxon Rank-Sum Test)

Description:
A non-parametric test used to compare differences between two independent groups when the dependent variable is either ordinal or continuous but not normally distributed.

Assumptions:

  • Independent observations.

  • Ordinal or continuous data.

  • Doesn’t require normal distribution.

When to Use:

  • Data is skewed or has outliers.

  • Sample sizes are small.

Example:
Comparing pain scores (non-normal data) between two different analgesic groups.

Discussion Thread Ideas:

  • Advantages of using Mann–Whitney over t-test.

  • How to interpret U values and p-values?

🔄 3. Wilcoxon Signed-Rank Test

Description:
A non-parametric test used for comparing two related samples or repeated measurements on a single sample to assess whether their population mean ranks differ.

Assumptions:

  • Paired data.

  • Symmetrical distribution of the differences.

  • Data at least ordinal.

When to Use:

  • Paired samples with non-normal distribution.

  • Pre-test and post-test designs.

Example:
Comparing cholesterol levels in patients before and after using a new drug.

Discussion Thread Ideas:

  • When to choose Wilcoxon over paired t-test?

  • Real-world examples using Wilcoxon signed-rank test.

 
Posted : 02/06/2025 11:52 am
Share:

    Get a Quote







    Price: $0