Statistics is the only math class where "getting the right number" is only half the battle. The other half is explaining what that number actually means in English. After grading 2,000+ midterms, I can tell you where students crash and burn.
Master Sampling Distributions First
Most people fail because they treat Sampling Distributions like just another chapter. They aren't. They are the bridge between descriptive stats (mean/median) and inferential stats (hypothesis testing). If you don't understand the Central Limit Theorem, nothing in the second half of the semester will make sense. You can't just memorize the formula; you need to grasp the concept of "Standard Error." Before you look to complete my statistics course with a passing grade, master this concept.
Conquer Hypothesis Testing Early
The Null Hypothesis ($H_0$) is counter-intuitive. You never "prove" it true; you only "fail to reject" it. It’s like a criminal trial—innocent until proven guilty. Professors love to trap students on Type I (False Positive) vs Type II (False Negative) errors. If you are struggling here, you might be tempted to ask "can I pay someone to take my statistics class". That's valid, but try drawing the rejection regions first. It helps.
Don't Fight the Software
Whether it's RStudio, SPSS, or MyStatLab, syntax errors will ruin your grade faster than bad math. A missing comma in R code is a zero. Using Excel when the professor demanded SAS is a zero. If the tech headaches are too much, that is usually when students decide to take my online statistics class for me.