STATISTICALLY SPEAKING

The professor told our class it should take no more than 2 hours to complete the final take home exam.

I don't know if I should be embarrassed or proud of the fact that it took me 28 hours to figure out the SPSS outputs and conclusions for 8 hypotheses.

Learning how to run a t-test, correlations, analyze variances with one-way ANOVA or factorial ANOVA, using linear regression to predict the future, and nonparametric tests over 6-weeks was the easy part.

The challenging part is translating a case study and figuring out which test to run and providing the interpretation of the values. 

In statistics, there is no such thing as proof; only proving what is false.

The entire science of statistics was developed to account for the error in every test.

A Type 1 error is rejecting the null hypothesis = there is a statistically significant difference.

A Type 2 error is failing to reject the null hypothesis = basically, accepting random chance.

It felt like taking accounting 101 and learning debits and credits for the first time.