π A Literature Gap = what existing studies have missed
π It could be:
β’ unanswered questions
β’ unexplored areas
β’ conflicting findings
π Your research fills that gap
#LiteratureReview#ResearchGaps#AcademicResearch
π Running a T-Test? Follow these steps:
1οΈβ£ State hypotheses
2οΈβ£ Check assumptions
3οΈβ£ Choose test type
4οΈβ£ Run test
5οΈβ£ Interpret p-value
Simple steps = accurate results βοΈ
#TTest#DataAnalysis#Statistics#ResearchMethods
π Running an ANOVA? Follow these steps:
1οΈβ£ Define groups
2οΈβ£ Check assumptions
3οΈβ£ Run ANOVA
4οΈβ£ Post-hoc tests
5οΈβ£ Interpret results
More than 2 groups? ANOVA is your go-to π₯
#ANOVA#Statistics#DataAnalysis#ResearchMethods
π Confidence Interval (CI) = range where the true value likely falls
Example: 95% CI β youβre 95% confident the value lies in that range
#ConfidenceInterval#Statistics#DataAnalysis
π Effect Size shows how strong a relationship or difference is not just if it exists.
Big difference β always meaningful
#EffectSize#Statistics#ResearchBeginner
π p-value = probability your result is due to chance
β p < 0.05 β significant
β p > 0.05 β not significant
Donβt just report it understand it!
#PValue#Statistics#ResearchBeginner
π Types of T-Tests
πΉ Independent T-Test β compares 2 different groups
πΉ Paired T-Test β compares same group (before vs after)
Choose wisely β it affects your results!
#TTest#Statistics#DataAnalysis#ResearchMethods