WOMEN TECHSTERS FELLOWSHIP-DATA SCIENCE AND ARTIFICIAL INTELLIGENCE WEEK 3
Jennifer Ezinne Onyebuchi (Tech Big Sis)
Artificial Intelligence for Social Good || Data Scientist || Founder, Tech Big Sis Foundation || Raising Africa's Next Generation of Tech Giants in Rural Communities and Slums || Women Techsters Fellow '24
In the third week (30th Oct to 2nd Nov) of our Data Science and AI classes, we continued with Statistics and Probability.
We explored additive rules, conditional probability, Baye’s theorem, conditional probability, normal distribution and paranormal distribution.
Furthermore we delved into central limit theorem and confidence intervals, sampling distribution and sample distribution, law of large numbers.
Then came Hypothesis testing
Hypothesis testing is a common statistical tool used in research and data science to support the certainty of findings. A hypothesis is often described as an “educated guess” about a specific parameter or population
We then further explored type 1 and type 2 errors as well as some Common hypothesis tests such as One sample t-test, Two-sample t-test, Paired t-test, One sample z-test, Two sample z-test.
And that’s a wrap for #statistics and #probability.
We mooveee (as seen in the pics)
Goodbye Stats, see you...
#WTFC24 #WomenTechstersFellowship #WomenTechsters #AfricanWomanInTechnology #Tech4Dev #MyWomenTechstersFellowshipClassof2024Story #MyWTFC24Story #Statistics #probability #momintech #womenintech #techbigsis