Watch how the FUTA Biomedical Engineering Class of 2025 helped an amputee of 13 years walk again, turning what they learnt in class into a life-changing solution.
The First Nigerian University to build a Satellite - FUTA
The First Space Scientist to send an agricultural crop from West Africa to Space - FUTA Alumnus
@ShrewdT3ch@renoomokri@swankieDiva His boss, Atiku also supported the girl, but Reno as he go be, he no fit come after his boss, everything he dey chew for mouth na about Obi
I imagined the CBN making Naira notes in honour of the late Prof Dora Akunyili and Dr. Stella Adadevoh
-The two most heroic Nigerians in the last 20 years (In my books).
So I designed these banknotes this evening.
# Alt_Text 👇🏽
ANOVA (Analysis of Variance) is a statistical test used to determine whether there are significant differences between the means of three or more groups. It helps answer: Are the group means statistically different from each other?
1. Null Hypothesis (H₀): All group means are equal.
2. Alternative Hypothesis (H₁): At least one group mean is different.
3. Use Case: When comparing more than two groups. If you only have two groups, a t-test is simpler.
ANOVA compares two types of variation:
1. Between-group variation: Differences between the group means.
2. Within-group variation: Variability of data points within each group.
If the between-group variation is much larger than the within-group variation, it suggests the means are significantly different.
Types of ANOVA:
1. One-way ANOVA: Tests the impact of one factor (e.g., comparing test scores across three teaching methods).
2. Two-way ANOVA: Tests the impact of two factors and their interaction (e.g., comparing test scores by teaching methods and gender).
Example: One-Way ANOVA
Scenario: You test three diets (A, B, C) to see if they lead to different weight loss results.
Data:
Group A: [4, 5, 6]
Group B: [7, 8, 9]
Group C: [3, 4, 5]
Steps:
1. Calculate the mean for each group.
2. Measure the variation between and within groups.
3. Compute the F-ratio (a statistic that compares the variations).
4. Check the F-value against a critical value or p-value:
If p-value < 0.05, reject the null hypothesis (significant difference exists).
ANOVA tells you if there's a difference but not which groups differ. For that, use a post-hoc test (e.g., Tukey's test).
Data should meet these assumptions:
1. Groups are independent.
2. Data is normally distributed.
3. Variances are roughly equal (homogeneity of variance).
@AFC_Zeke_ @Macardzie@Squawka Pls what’s White now doing since you don’t rely on him when it comes to defending, you also don’t rely on going forward consistently. Is he just there to make up the 11th player?